In this paper, symmetric scanned linear antenna arrays are synthesized, in order to minimize the side lobe level of the radiation pattern. The feeding current amplitudes are considered as the optimization parameters. Newly proposed optimization algorithms are presented to achieve our target; Antlion Optimization (ALO) and a new hybrid algorithm. Three different examples are illustrated in this paper; 20, 26 and 30 elements scanned linear antenna array. The obtained results prove the effectiveness and the ability of the proposed algorithms to outperform and compete other algorithms like Symbiotic Organisms Search (SOS) and Firefly Algorithm (FA).
Economic/Emission Load Dispatch Using Artificial Bee Colony AlgorithmIDES Editor
This paper presents an application of the
artificial bee colony (ABC) algorithm to multi-objective
optimization problems in power system. A new multiobjective
artificial bee colony (MOABC) algorithm to
solve the economic/ emission dispatch (EED) problem is
proposed in this paper. Non-dominated sorting is
employed to obtain a Pareto optimal set. Moreover, fuzzy
decision theory is employed to extract the best
compromise solution. A numerical result for IEEE 30-bus
test system is presented to demonstrate the capability of
the proposed approach to generate well-distributed
Pareto-optimal solutions of EED problem in one single
run. In addition, the EED problem is also solved using the
weighted sum method using ABC. Results obtained with
the proposed approach are compared with other
techniques available in the literature. Results obtained
show that the proposed MOABC has a great potential in
handling multi-objective optimization problem.
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...ijceronline
The performances of the statistical methods of time series forecast can be improved by precise selection of their parameters. Various techniques are being applied to improve the modeling accuracy of these models. Particle swarm optimization is one such technique which can be conveniently used to determine the model parameters accurately. This robust optimization technique has already been applied to improve the performance of artificial neural networks for time series prediction. This study uses particle swarm optimization technique to determine the parameters of an exponential autoregressive model for time series prediction. The model is applied for annual rainfall prediction and it shows a fairly good performance in comparison to the statistical ARIMA model
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
In this study, optimal economic load dispatch problem (OELD) is resolved by
a novel improved algorithm. The proposed modified moth swarm algorithm
(MMSA), is developed by proposing two modifications on the classical moth
swarm algorithm (MSA). The first modification applies an effective formula
to replace an ineffective formula of the mutation technique. The second
modification is to cancel the crossover technique. For proving the efficient
improvements of the proposed method, different systems with discontinuous
objective functions as well as complicated constraints are used. Experiment
results on the investigated cases show that the proposed method can get less
cost and achieve stable search ability than MSA. As compared to other
previous methods, MMSA can archive equal or better results. From this view,
it can give a conclusion that MMSA method can be valued as a useful method
for OELD problem.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Bi-objective Optimization Apply to Environment a land Economic Dispatch Probl...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Economic/Emission Load Dispatch Using Artificial Bee Colony AlgorithmIDES Editor
This paper presents an application of the
artificial bee colony (ABC) algorithm to multi-objective
optimization problems in power system. A new multiobjective
artificial bee colony (MOABC) algorithm to
solve the economic/ emission dispatch (EED) problem is
proposed in this paper. Non-dominated sorting is
employed to obtain a Pareto optimal set. Moreover, fuzzy
decision theory is employed to extract the best
compromise solution. A numerical result for IEEE 30-bus
test system is presented to demonstrate the capability of
the proposed approach to generate well-distributed
Pareto-optimal solutions of EED problem in one single
run. In addition, the EED problem is also solved using the
weighted sum method using ABC. Results obtained with
the proposed approach are compared with other
techniques available in the literature. Results obtained
show that the proposed MOABC has a great potential in
handling multi-objective optimization problem.
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...ijceronline
The performances of the statistical methods of time series forecast can be improved by precise selection of their parameters. Various techniques are being applied to improve the modeling accuracy of these models. Particle swarm optimization is one such technique which can be conveniently used to determine the model parameters accurately. This robust optimization technique has already been applied to improve the performance of artificial neural networks for time series prediction. This study uses particle swarm optimization technique to determine the parameters of an exponential autoregressive model for time series prediction. The model is applied for annual rainfall prediction and it shows a fairly good performance in comparison to the statistical ARIMA model
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
In this study, optimal economic load dispatch problem (OELD) is resolved by
a novel improved algorithm. The proposed modified moth swarm algorithm
(MMSA), is developed by proposing two modifications on the classical moth
swarm algorithm (MSA). The first modification applies an effective formula
to replace an ineffective formula of the mutation technique. The second
modification is to cancel the crossover technique. For proving the efficient
improvements of the proposed method, different systems with discontinuous
objective functions as well as complicated constraints are used. Experiment
results on the investigated cases show that the proposed method can get less
cost and achieve stable search ability than MSA. As compared to other
previous methods, MMSA can archive equal or better results. From this view,
it can give a conclusion that MMSA method can be valued as a useful method
for OELD problem.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Bi-objective Optimization Apply to Environment a land Economic Dispatch Probl...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
FORECASTING ENERGY CONSUMPTION USING FUZZY TRANSFORM AND LOCAL LINEAR NEURO F...ijsc
This paper proposes a hybrid approach based on local linear neuro fuzzy (LLNF) model and fuzzy transform (F-transform), termed FT-LLNF, for prediction of energy consumption. LLNF models are powerful in modelling and forecasting highly nonlinear and complex time series. Starting from an optimal
linear least square model, they add nonlinear neurons to the initial model as long as the model's accuracy is improved. Trained by local linear model tree learning (LOLIMOT) algorithm, the LLNF models provide maximum generalizability as well as the outstanding performance. Besides, the recently introduced technique of fuzzy transform (F-transform) is employed as a time series pre-processing method. The
technique of F-transform, established based on the concept of fuzzy partitions, eliminates noisy variations of the original time series and results in a well-behaved series which can be predicted with higher accuracy. The proposed hybrid method of FT-LLNF is applied to prediction of energy consumption in the
United States and Canada. The prediction results and comparison to optimized multi-layer perceptron (MLP) models and the LLNF itself, revealed the promising performance of the proposed approach for energy consumption prediction and its potential usage for real world applications.
The problem of power system optimization has become a deciding factor in electrical power system engineering practice with emphasis on cost and emission reduction. The economic emission dispatch (EED) problem has been addressed in this paper using a Biogeography-based optimization (BBO). The BBO is inspired by geographical distribution of species within islands. This optimization algorithm works on the basis of two concepts-migration and mutation. In this paper a non-uniform mutation operator has been employed. The proposed technique shows better diversified search process and hence finds solutions more accurately with high convergence rate. The BBO with new mutation operator is tested on ten unit system. The comparison which is based on efficiency, reliability and accuracy shows that proposed mutation operator is competitive to the present one.
techTransmission usage and cost allocation using shapley value and tracing me...elelijjournal
In the deregulated power system, transmission pricing has become a very important task because it is necessary to develop an efficient, feasible and reliable pricing scheme that can generate the useful economic signals to network users such as generating companies, transmission companies, distribution companies and customers. The objective of this paper is to compare transmission usage and cost allocation scheme to loads (and/or generators) based on Shapley value method and power flow tracing method.Modified Kirchhoff matrix is used for power flow tracing. A comparison is done between the both methods.
A case study based on sample 6 bus power system is applied to check the feasibility and reliability of the proposed usage and cost allocation methodology.
GWO-based estimation of input-output parameters of thermal power plantsTELKOMNIKA JOURNAL
The fuel cost curve of thermal generators was very important in the calculation of economic dispatch and optimal power flow. Temperature and aging could make changes to fuel cost curve so curve estimation need to be done periodically. The accuracy of the curve parameters estimation strongly affected the calculation of the dispatch. This paper aims to estimate the fuel cost curve parameters by using the grey wolf optimizer method. The problem of curve parameter estimation was made as an optimization problem. The objective function to be minimized was the total number of absolute error or the difference between the actual value and the estimated value of the fuel cost function. The estimated values of parameter that produce the smallest total absolute error were the values of final solution. The simulation results showed that parameter estimation using gray wolf optimizer method further minimized the value of objective function. By using three models of fuel cost curve and given test data, parameter estimation using grey wolf optimizer method produced the better estimation results than those estimation results obtained using least square error, particle swarm optimization, genetic algorithm, artificial bee colony and cuckoo search methods.
OPTIMIZATION OF COST 231 MODEL FOR 3G WIRELESS COMMUNICATION SIGNAL IN SUBURB...Onyebuchi nosiri
ABSTRACT Radio propagation models are important tools adopted for the characterization and optimization of wireless communication signals in a propagation environment. In this paper, the Cost 231 model was optimized for 3G wireless communication signal in Aggrey Road (04˚ 45̀ .06˝N, 07˚ 02̀ .24˝E), a suburban area in Port Harcourt, Nigeria. Phone-Based Drive Test was adopted for field measurement using TEMS 11 network simulator. The optimization process was implemented through the use of Least Square Algorithm taking into account the initial offset parameters and the slope of the model curve in Cost 231 model for the process. The performance of the optimized model using the statistical tools in Minitab-14 software was evaluated for the Mean Absolute Deviation (MAD) and the Mean Squared Deviation (MSD) respectively. The results obtained demonstrated the following parametric values: 1.196, 2.01 and 1.179, 1.94 for Cost 231 and Optimized models respectively. The optimized model is recommended for deployment for a better and accurate path loss prediction on the environment of study.
Offine/Online Optimum Routing of a UAV using Auxiliary Points IJECEIAES
This paper presents a method to determine the route of a three-dimensional UAV. Three criteria; the height, the length of flight path and the un authorized areas are used as the constraints and combined in a fuzzy function as the evaluation function. The article aimed to discover a minimum cost route from source to destination considering the constrains. In this paper a new searching methodis proposed, with use of auxiliary points. The auxiliary point method iterativelydivides a straight line to two shorter lines with less cost of evaluation function. Implementation results show that the proposed method dramatically decreasesthe calculations; meanwhile the ight route is sub-optimum.
A MODIFIED ANT COLONY ALGORITHM FOR SOLVING THE UNIT COMMITMENT PROBLEMaeijjournal
Solving the unit commitment (UC) problem is one of the most complicated issues in power systems that its
exact solving can be calculated by perfect counting of entire possible compounds of generative units. UC is
equated as a nonlinear optimization with huge size. Purpose of solving this problem is to programming the
optimization of the generative units to minimize the full action cost regarding problem constraints. In this
article, a modified version of ant colony optimization (MACO) is introduced for solving the UC problem in
a power system. ACO algorithm is a powerful optimization method which has the capability of fleeing from
local minimums by performing flexible memory system. The efficiency of proposed method in two power
system containing 4 and 10 generative units is indicated. Comparison of obtained results from the proposed
method with results of the past well-known methods is a proof for suitability of performing the introduced
algorithm in economic input and output of generative units.
Solving practical economic load dispatch problem using crow search algorithm IJECEIAES
The practical economic load dispatch problem is a non-convex, non-smooth, and non-linear optimization problem due to including practical considerations such as valve-point loading effects and multiple fuel options. An optimization algorithm named crow search algorithm is proposed in this paper to solve the practical non-convex economic load dispatch problem. Three cases with different economic load dispatch configurations are studied. The simulation results and statistical analysis show the efficiency of the proposed crow search algorithm. Also, the simulation results are compared to the other reported algorithms. The comparison of results confirms the high-quality solutions and the effectiveness of the proposed algorithm for solving the non-convex practical economic load dispatch problem.
The behaviour of ACS-TSP algorithm when adapting both pheromone parameters us...IJECEIAES
In this paper, an evolved ant colony system (ACS) is proposed by dynamically adapting the responsible parameters for the decay of the pheromone trails 휉 and 휌 using fuzzy logic controller (FLC) applied in the travelling salesman problems (TSP). The purpose of the proposed method is to understand the effect of both parameters 휉 and 휌 on the performance of the ACS at the level of solution quality and convergence speed towards the best solutions through studying the behaviour of the ACS algorithm during this adaptation. The adaptive ACS is compared with the standard one. Computational results show that the adaptive ACS with dynamic adaptation of local pheromone parameter 휉 is more effective compared to the standard ACS.
Exhaust System Muffler Volume Optimization of Light Commercial passenger Car ...Barhm Mohamad
Nowadays, the automotive industry is focused on weight and size reduction. Main advantage of this weight and size reduction are improving the fuel economy. The specific fuel consumption of a vehicle can be improved through e.g. downsizing area of heat loss, if we focus on vehicle with weight reduction. Weight reduction can be done by replacing material or by changing the size (dimensions) of components. In the present work we have focused on Audi A6 muffler, troubleshooting and optimizing the muffler by changing pipe length of inlet and outlet, also by replacing the original mesh plate to porous pipe. Based on optimization, prototype has been built with the help of 3D design tool CATIA V5 and the calculations of transmission loss (TL) have been performed by MATLAB. Plane wave-based models such as the transfer matrix method (TMM) can offer fast initial prototype solutions for muffler designers. The principles of TMM for predicting the transmission loss of a muffler was used. Result of this present study of an existing muffler has been analysed and then compared with vehicle level test observation data. Noise level have been optimized for new muffler design. Other literatures were played significant rule for validate our results.
Comparative and comprehensive study of linear antenna arrays’ synthesisIJECEIAES
In this paper, a comparative and comprehensive study of synthesizing linear antenna array (LAA) designs, is presented. Different desired objectives are considered in this paper; reducing the maximum sidelobe radiation pattern (i.e., pencil-beam pattern), controlling the first null beamwidth (FNBW), and imposing nulls at specific angles in some designs, which are accomplished by optimizing different array parameters (feed current amplitudes, feed current phase, and array elements positions). Three different optimization algorithms are proposed in order to achieve the wanted goals; grasshopper optimization algorithms (GOA), ant lion optimization (ALO), and a new hybrid optimization algorithm based on GOA and ALO. The obtained results show the effectiveness and robustness of the proposed algorithms to achieve the wanted targets. In most experiments, the proposed algorithms outperform other well-known optimization methods, such as; Biogeography based optimization (BBO), particle swarm optimization (PSO), firefly algorithm (FA), cuckoo search (CS) algorithm, genetic algorithm (GA), Taguchi method, self-adaptive differential evolution (SADE), modified spider monkey optimization (MSMO), symbiotic organisms search (SOS), enhanced firefly algorithm (EFA), bat flower pollination (BFP) and tabu search (TS) algorithm.
In the recent years the development in communication systems requires the development of low cost, minimal weight, low profile antennas that are capable of maintaining high performance over a wide spectrum of frequencies. This technological trend has focused much effort into the design of a micro strip patch antennas. Nowadays Evolutionary Computation has its growth to extent. Generally electromagnetic optimization problems generally involve a large number of parameters. Synthesis of non-uniform linear antenna arrays is one of the most important electromagnetic optimization problems of the current interest.
Synthesis of new antenna arrays with arbitrary geometries based on the super...IJECEIAES
The synthesis of antenna arrays with low sidelobe levels is needed to enhance the communication systems’ efficiency. In this paper, new arbitrary geometries that improve the ability of the antenna arrays to minimize the sidelobe level, are proposed. We employ the well-known superformula equation in the antenna arrays field by implementing the equation in the general array factor equation. Three metaheuristic optimization algorithms are used to synthesize the antenna arrays and their geometries; antlion optimization (ALO) algorithm, grasshopper optimization algorithm (GOA), and a new hybrid algorithm based on ALO and GOA. All the proposed algorithms are high-performance computational methods, which proved their efficiency for solving different real-world optimization problems. 15 design examples are presented and compared to prove validity with the most general standard geometry: elliptical antenna array (EAA). It is observed that the proposed geometries outperform EAA geometries by 4.5 dB and 10.9 dB in the worst and best scenarios, respectively, which proves the advantage and superiority of our approach.
Ant Colony Optimization for Optimal Low-Pass State Variable Filter Sizing IJECEIAES
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.
Enhancing radial distribution system performance by optimal placement of DST...IJECEIAES
In this paper, A novel modified optimization method was used to find the optimal location and size for placing distribution Static Compensator in the radial distribution test feeder in order to improve its performance by minimizing the total power losses of the test feeder, enhancing the voltage profile and reducing the costs. The modified grey wolf optimization algorithm is used for the first time to solve this kind of optimization problem. An objective function was developed to study the radial distribution system included total power loss of the system and costs due to power loss in system. The proposed method is applied to two different test distribution feeders (33 bus and 69 bus test systems) using different Dstatcom sizes and the acquired results were analyzed and compared to other recent optimization methods applied to the same test feeders to ensure the effectiveness of the used method and its superiority over other recent optimization mehods. The major findings from obtained results that the applied technique found the most minimized total power loss in system, the best improved voltage profile and most reduction in costs due power loss compared to other methods.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
FORECASTING ENERGY CONSUMPTION USING FUZZY TRANSFORM AND LOCAL LINEAR NEURO F...ijsc
This paper proposes a hybrid approach based on local linear neuro fuzzy (LLNF) model and fuzzy transform (F-transform), termed FT-LLNF, for prediction of energy consumption. LLNF models are powerful in modelling and forecasting highly nonlinear and complex time series. Starting from an optimal
linear least square model, they add nonlinear neurons to the initial model as long as the model's accuracy is improved. Trained by local linear model tree learning (LOLIMOT) algorithm, the LLNF models provide maximum generalizability as well as the outstanding performance. Besides, the recently introduced technique of fuzzy transform (F-transform) is employed as a time series pre-processing method. The
technique of F-transform, established based on the concept of fuzzy partitions, eliminates noisy variations of the original time series and results in a well-behaved series which can be predicted with higher accuracy. The proposed hybrid method of FT-LLNF is applied to prediction of energy consumption in the
United States and Canada. The prediction results and comparison to optimized multi-layer perceptron (MLP) models and the LLNF itself, revealed the promising performance of the proposed approach for energy consumption prediction and its potential usage for real world applications.
The problem of power system optimization has become a deciding factor in electrical power system engineering practice with emphasis on cost and emission reduction. The economic emission dispatch (EED) problem has been addressed in this paper using a Biogeography-based optimization (BBO). The BBO is inspired by geographical distribution of species within islands. This optimization algorithm works on the basis of two concepts-migration and mutation. In this paper a non-uniform mutation operator has been employed. The proposed technique shows better diversified search process and hence finds solutions more accurately with high convergence rate. The BBO with new mutation operator is tested on ten unit system. The comparison which is based on efficiency, reliability and accuracy shows that proposed mutation operator is competitive to the present one.
techTransmission usage and cost allocation using shapley value and tracing me...elelijjournal
In the deregulated power system, transmission pricing has become a very important task because it is necessary to develop an efficient, feasible and reliable pricing scheme that can generate the useful economic signals to network users such as generating companies, transmission companies, distribution companies and customers. The objective of this paper is to compare transmission usage and cost allocation scheme to loads (and/or generators) based on Shapley value method and power flow tracing method.Modified Kirchhoff matrix is used for power flow tracing. A comparison is done between the both methods.
A case study based on sample 6 bus power system is applied to check the feasibility and reliability of the proposed usage and cost allocation methodology.
GWO-based estimation of input-output parameters of thermal power plantsTELKOMNIKA JOURNAL
The fuel cost curve of thermal generators was very important in the calculation of economic dispatch and optimal power flow. Temperature and aging could make changes to fuel cost curve so curve estimation need to be done periodically. The accuracy of the curve parameters estimation strongly affected the calculation of the dispatch. This paper aims to estimate the fuel cost curve parameters by using the grey wolf optimizer method. The problem of curve parameter estimation was made as an optimization problem. The objective function to be minimized was the total number of absolute error or the difference between the actual value and the estimated value of the fuel cost function. The estimated values of parameter that produce the smallest total absolute error were the values of final solution. The simulation results showed that parameter estimation using gray wolf optimizer method further minimized the value of objective function. By using three models of fuel cost curve and given test data, parameter estimation using grey wolf optimizer method produced the better estimation results than those estimation results obtained using least square error, particle swarm optimization, genetic algorithm, artificial bee colony and cuckoo search methods.
OPTIMIZATION OF COST 231 MODEL FOR 3G WIRELESS COMMUNICATION SIGNAL IN SUBURB...Onyebuchi nosiri
ABSTRACT Radio propagation models are important tools adopted for the characterization and optimization of wireless communication signals in a propagation environment. In this paper, the Cost 231 model was optimized for 3G wireless communication signal in Aggrey Road (04˚ 45̀ .06˝N, 07˚ 02̀ .24˝E), a suburban area in Port Harcourt, Nigeria. Phone-Based Drive Test was adopted for field measurement using TEMS 11 network simulator. The optimization process was implemented through the use of Least Square Algorithm taking into account the initial offset parameters and the slope of the model curve in Cost 231 model for the process. The performance of the optimized model using the statistical tools in Minitab-14 software was evaluated for the Mean Absolute Deviation (MAD) and the Mean Squared Deviation (MSD) respectively. The results obtained demonstrated the following parametric values: 1.196, 2.01 and 1.179, 1.94 for Cost 231 and Optimized models respectively. The optimized model is recommended for deployment for a better and accurate path loss prediction on the environment of study.
Offine/Online Optimum Routing of a UAV using Auxiliary Points IJECEIAES
This paper presents a method to determine the route of a three-dimensional UAV. Three criteria; the height, the length of flight path and the un authorized areas are used as the constraints and combined in a fuzzy function as the evaluation function. The article aimed to discover a minimum cost route from source to destination considering the constrains. In this paper a new searching methodis proposed, with use of auxiliary points. The auxiliary point method iterativelydivides a straight line to two shorter lines with less cost of evaluation function. Implementation results show that the proposed method dramatically decreasesthe calculations; meanwhile the ight route is sub-optimum.
A MODIFIED ANT COLONY ALGORITHM FOR SOLVING THE UNIT COMMITMENT PROBLEMaeijjournal
Solving the unit commitment (UC) problem is one of the most complicated issues in power systems that its
exact solving can be calculated by perfect counting of entire possible compounds of generative units. UC is
equated as a nonlinear optimization with huge size. Purpose of solving this problem is to programming the
optimization of the generative units to minimize the full action cost regarding problem constraints. In this
article, a modified version of ant colony optimization (MACO) is introduced for solving the UC problem in
a power system. ACO algorithm is a powerful optimization method which has the capability of fleeing from
local minimums by performing flexible memory system. The efficiency of proposed method in two power
system containing 4 and 10 generative units is indicated. Comparison of obtained results from the proposed
method with results of the past well-known methods is a proof for suitability of performing the introduced
algorithm in economic input and output of generative units.
Solving practical economic load dispatch problem using crow search algorithm IJECEIAES
The practical economic load dispatch problem is a non-convex, non-smooth, and non-linear optimization problem due to including practical considerations such as valve-point loading effects and multiple fuel options. An optimization algorithm named crow search algorithm is proposed in this paper to solve the practical non-convex economic load dispatch problem. Three cases with different economic load dispatch configurations are studied. The simulation results and statistical analysis show the efficiency of the proposed crow search algorithm. Also, the simulation results are compared to the other reported algorithms. The comparison of results confirms the high-quality solutions and the effectiveness of the proposed algorithm for solving the non-convex practical economic load dispatch problem.
The behaviour of ACS-TSP algorithm when adapting both pheromone parameters us...IJECEIAES
In this paper, an evolved ant colony system (ACS) is proposed by dynamically adapting the responsible parameters for the decay of the pheromone trails 휉 and 휌 using fuzzy logic controller (FLC) applied in the travelling salesman problems (TSP). The purpose of the proposed method is to understand the effect of both parameters 휉 and 휌 on the performance of the ACS at the level of solution quality and convergence speed towards the best solutions through studying the behaviour of the ACS algorithm during this adaptation. The adaptive ACS is compared with the standard one. Computational results show that the adaptive ACS with dynamic adaptation of local pheromone parameter 휉 is more effective compared to the standard ACS.
Exhaust System Muffler Volume Optimization of Light Commercial passenger Car ...Barhm Mohamad
Nowadays, the automotive industry is focused on weight and size reduction. Main advantage of this weight and size reduction are improving the fuel economy. The specific fuel consumption of a vehicle can be improved through e.g. downsizing area of heat loss, if we focus on vehicle with weight reduction. Weight reduction can be done by replacing material or by changing the size (dimensions) of components. In the present work we have focused on Audi A6 muffler, troubleshooting and optimizing the muffler by changing pipe length of inlet and outlet, also by replacing the original mesh plate to porous pipe. Based on optimization, prototype has been built with the help of 3D design tool CATIA V5 and the calculations of transmission loss (TL) have been performed by MATLAB. Plane wave-based models such as the transfer matrix method (TMM) can offer fast initial prototype solutions for muffler designers. The principles of TMM for predicting the transmission loss of a muffler was used. Result of this present study of an existing muffler has been analysed and then compared with vehicle level test observation data. Noise level have been optimized for new muffler design. Other literatures were played significant rule for validate our results.
Comparative and comprehensive study of linear antenna arrays’ synthesisIJECEIAES
In this paper, a comparative and comprehensive study of synthesizing linear antenna array (LAA) designs, is presented. Different desired objectives are considered in this paper; reducing the maximum sidelobe radiation pattern (i.e., pencil-beam pattern), controlling the first null beamwidth (FNBW), and imposing nulls at specific angles in some designs, which are accomplished by optimizing different array parameters (feed current amplitudes, feed current phase, and array elements positions). Three different optimization algorithms are proposed in order to achieve the wanted goals; grasshopper optimization algorithms (GOA), ant lion optimization (ALO), and a new hybrid optimization algorithm based on GOA and ALO. The obtained results show the effectiveness and robustness of the proposed algorithms to achieve the wanted targets. In most experiments, the proposed algorithms outperform other well-known optimization methods, such as; Biogeography based optimization (BBO), particle swarm optimization (PSO), firefly algorithm (FA), cuckoo search (CS) algorithm, genetic algorithm (GA), Taguchi method, self-adaptive differential evolution (SADE), modified spider monkey optimization (MSMO), symbiotic organisms search (SOS), enhanced firefly algorithm (EFA), bat flower pollination (BFP) and tabu search (TS) algorithm.
In the recent years the development in communication systems requires the development of low cost, minimal weight, low profile antennas that are capable of maintaining high performance over a wide spectrum of frequencies. This technological trend has focused much effort into the design of a micro strip patch antennas. Nowadays Evolutionary Computation has its growth to extent. Generally electromagnetic optimization problems generally involve a large number of parameters. Synthesis of non-uniform linear antenna arrays is one of the most important electromagnetic optimization problems of the current interest.
Synthesis of new antenna arrays with arbitrary geometries based on the super...IJECEIAES
The synthesis of antenna arrays with low sidelobe levels is needed to enhance the communication systems’ efficiency. In this paper, new arbitrary geometries that improve the ability of the antenna arrays to minimize the sidelobe level, are proposed. We employ the well-known superformula equation in the antenna arrays field by implementing the equation in the general array factor equation. Three metaheuristic optimization algorithms are used to synthesize the antenna arrays and their geometries; antlion optimization (ALO) algorithm, grasshopper optimization algorithm (GOA), and a new hybrid algorithm based on ALO and GOA. All the proposed algorithms are high-performance computational methods, which proved their efficiency for solving different real-world optimization problems. 15 design examples are presented and compared to prove validity with the most general standard geometry: elliptical antenna array (EAA). It is observed that the proposed geometries outperform EAA geometries by 4.5 dB and 10.9 dB in the worst and best scenarios, respectively, which proves the advantage and superiority of our approach.
Ant Colony Optimization for Optimal Low-Pass State Variable Filter Sizing IJECEIAES
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.
Enhancing radial distribution system performance by optimal placement of DST...IJECEIAES
In this paper, A novel modified optimization method was used to find the optimal location and size for placing distribution Static Compensator in the radial distribution test feeder in order to improve its performance by minimizing the total power losses of the test feeder, enhancing the voltage profile and reducing the costs. The modified grey wolf optimization algorithm is used for the first time to solve this kind of optimization problem. An objective function was developed to study the radial distribution system included total power loss of the system and costs due to power loss in system. The proposed method is applied to two different test distribution feeders (33 bus and 69 bus test systems) using different Dstatcom sizes and the acquired results were analyzed and compared to other recent optimization methods applied to the same test feeders to ensure the effectiveness of the used method and its superiority over other recent optimization mehods. The major findings from obtained results that the applied technique found the most minimized total power loss in system, the best improved voltage profile and most reduction in costs due power loss compared to other methods.
Radio-frequency circular integrated inductors sizing optimization using bio-...IJECEIAES
In this article, a comparative study is accomplished between three of the most used swarm intelligence (SI) techniques; namely artificial bee colony (ABC), ant colony optimization (ACO), and particle swarm optimization (PSO) to carry out the optimal design of radio-frequency (RF) spiral inductors, the three algorithms are applied to the cost function of RF circular inductors for 180 nm beyond 2.50 GHz, the aim is to ensure optimal performance with less error in inductance, and a high-quality factor when compared to electromagnetic simulation. Simulation experiments are achieved and performances regarding convergence velocity, robustness, and computing time are checked. Also, this paper shows an impact study of technological parameters and geometric features on the inductance and the quality factor of the studied integrated inductor. The building method of constraints design with algorithms used has given good results and electromagnetic simulations are of good accuracy with an error of 2.31% and 4.15% on the quality factor and inductance respectively. The simulation shows that ACO provides more accuracy in circuit size and fewer errors than ABC and PSO, while PSO and ABC are better in terms of convergence velocity.
performance analysis of different radiation pattern using genetic algorithmijtsrd
In most applications of antenna arrays, side lobe levels SLLs are commonly unwanted. Especially, the first side lobe level which determines maximum SLL is the main source of electromagnetic interference EMI , and hence, it should be lowered. In this thesis proposed a very simple and powerful method for the synthesis of linear array antenna. This method reduced the desired level of side lobe level SLL as well as to steer the main beam at different different angle. In this paper we draw the radiation pattern for N = 24 elements with main beam are shifted by 30° and the simulation result analysis by Matlab R2013a tool. Rahul Pandya | Praveen Kumar Patidar "Performance Analysis of Different Radiation Pattern using Genetic Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33020.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/33020/performance-analysis-of-different-radiation-pattern-using-genetic-algorithm/rahul-pandya
Economic and Emission Dispatch using Whale Optimization Algorithm (WOA) IJECEIAES
This paper work present one of the latest meta heuristic optimization approaches named whale optimization algorithm as a new algorithm developed to solve the economic dispatch problem. The execution of the utilized algorithm is analyzed using standard test system of IEEE 30 bus system. The proposed algorithm delivered optimum or near optimum solutions. Fuel cost and emission costs are considered together to get better result for economic dispatch. The analysis shows good convergence property for WOA and provides better results in comparison with PSO. The achieved results in this study using the above-mentioned algorithm have been compared with obtained results using other intelligent methods such as particle swarm Optimization. The overall performance of this algorithm collates with early proven optimization methodology, Particle Swarm Optimization (PSO). The minimum cost for the generation of units is obtained for the standard bus system.
Elements Space and Amplitude Perturbation Using Genetic Algorithm for Antenna...CSCJournals
A simple and fast genetic algorithm (GA) developed to reduce the sidelobes in non-uniformly spaced linear antenna arrays. The proposed GA algorithm optimizes two vectors of variables to increase the Main lobe to Sidelobe power ratio (M/S) of array’s radiation pattern. The algorithm, in the first phase calculates the positions of the array elements and in the second phase, it manipulates the amplitude of excitation signals for each element. The simulations performed for 16 and 24 elements array structure. The results indicated that M/S improved in first phase from 13.2 to over 22.2dB meanwhile the half power beamwidth (HPBW) left almost unchanged. After element replacement, in the second phase, by using amplitude tapering further improvement up to 32dB was achieved. Also, the simulations shown that after element space perturbation, some antenna elements can be merged together without any performance degradation in radiation pattern in terms of gain and sidelobes level.
A genetic algorithm for the optimal design of a multistage amplifier IJECEIAES
The optimal sizing of analog circuits is one of the most complicated processes, because of the number of variables taken into, to the number of required objectives to be optimized and to the constraint functions restrictions. The aim is to automate this activity in order to accelerate the circuits design and sizing. In this paper, we deal with the optimization of the three stage bipolar transistor amplifier performances namely the voltage gain (AV), the input impedance (ZIN), the output impedance (ZOUT), the power consumption (P) and the low and the high cutoff frequency (FL,FH), through the Genetic Algorithm (GA). The presented optimization problem is of multi-dimensional parameters, and the trade-off of all parameters. In fact, the passive components (Resistors and Capacitors) are selected from manufactured constant values (E12, E24, E48, E96, E192) for the purpose of reduce the cost of design; also, the intrinsic parameters of transistors (hybrid parameters and the junction capacitances) are considered variables in order not to be limited in design. SPICE simulation is used to validate the obtained result/performances.
For high performance communication systems, Side Lobe Level (SLL) reduction and improved directivity are the goal of antenna designers. In the recent years, many optimization techniques of antenna design are occupying demanding place over the analytical techniques. Though they have contributed attractive solutions, it is often obvious to select one that meets the particular design need at hand. In this paper, an optimization technique called Self-adaptive Differential Evolution (SaDE) that can be able to learn and behave intelligently along with hyper beam forming is integrated to determine an optimal set of excitation weights in the design of EcAA. Non-uniform excitation weights of the individual array elements of EcAA are performed to obtain reduced SLL, high directivity and flexible radiation pattern. To evaluate the improved performance of the proposed SaDE optimized hyper beam, comparison are done with uniformly excited, SaDE without hyper beam and Genetic Algorithm (GA). In general, the proposed work of pattern synthesis has resulted in much better reduction of SLL and FNBW than both the uniformly excited and thinned EcAA. The results of this study clearly reveal that the SLL highly reduced at a very directive beamwidth.
Optimal electric distribution network configuration using adaptive sunflower ...journalBEEI
Network reconfiguration (NR) is a powerful approach for power loss reduction in the distribution system. This paper presents a method of network reconfiguration using adaptive sunflower optimization (ASFO) to minimize power loss of the distribution system. ASFO is developed based on the original sunflower optimization (SFO) that is inspired from moving of sunflower to the sun. In ASFO, the mechanisms including pollination, survival and mortality mechanisms have been adjusted compared to the original SFO to fit with the network reconfiguration problem. The numerical results on the 14-node and 33-node systems have shown that ASFO outperforms to SFO for finding the optimal network configuration with greater success rate and better obtained solution quality. The comparison results with other previous approaches also indicate that ASFO has better performance than other methods in term of optimal network configuration. Thus, ASFO is a powerful method for the NR.
Application of genetic algorithm to the optimization of resonant frequency of...IOSR Journals
Abstract : Microstrip antenna is gathering a lot of interest in communication systems. Genetic algorithm is a popular optimization technique and has been introduced for design optimization of microstrip patch antenna. In this paper, genetic algorithm has been used for optimization of resonant frequency of coaxially fed rectangular microstrip antenna. The investigation is made at 3 different frequencies 3GHz, 5GHz and 10GHz respectively. Patch length, patch width & feed position are taken as optimization parameters. Return loss and radiation pattern for the optimized antenna are verified using IE3D software. Accuracy of the results encourages the use of genetic algorithm. Keywords - Rectangular microstrip antenna, genetic algorithm, resonant frequency, IE3D
Application of genetic algorithm to the optimization of resonant frequency of...IOSR Journals
Microstrip antenna is gathering a lot of interest in communication systems. Genetic algorithm is a
popular optimization technique and has been introduced for design optimization of microstrip patch antenna. In
this paper, genetic algorithm has been used for optimization of resonant frequency of coaxially fed rectangular
microstrip antenna. The investigation is made at 3 different frequencies 3GHz, 5GHz and 10GHz respectively.
Patch length, patch width & feed position are taken as optimization parameters. Return loss and radiation
pattern for the optimized antenna are verified using IE3D software. Accuracy of the results encourages the use
of genetic algorithm.
Chaotic based Pteropus algorithm for solving optimal reactive power problemIJAAS Team
In this work, a Chaotic based Pteropus algorithm (CPA) has been proposed for solving optimal reactive power problem. Pteropus algorithm imitates deeds of the Pteropus. Normally Pteropus while flying it avoid obstacles by using sonar echoes, particularly utilize time delay. To the original Pteropus algorithm chaotic disturbance has been applied and the optimal capability of the algorithm has been improved in search of global solution. In order to augment the population diversity and prevent early convergence, adaptively chaotic disturbance is added at the time of stagnation. Furthermore, exploration and exploitation capability of the proposed algorithm has been improved. Proposed CPA technique has been tested in standard IEEE 14,300 bus systems & real power loss has been considerably reduced.
Implementation of Digital Beamforming Technique for Linear Antenna Arraysijsrd.com
A digital Beamforming technique used for increased channel capacity and also increased signal to noise and interference ratio. In smart antenna, different type of radiation pattern of an antenna can be changed either by selecting appropriate weights or by changing the array geometry. This paper presented based on auxiliary phase algorithm by using this algorithm in linear antenna array determine the array pattern approximating the auxiliary function in both amplitude and phase. Cost function involving auxiliary function and array pattern is minimized by modifying the pattern.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
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Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
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Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
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2. ISSN: 2088-8708
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1478
Antlion Optimization (ALO) algorithm [18] and new proposed hybrid optimization algorithm based on
Grasshopper Optimization Algorithm (GOA) [19] and ALO.
The rest of this paper is organized as follows: In section 2, the proposed hybrid algorithm is
presented. In section 3, the geometry and problem formulation for the scanned antenna arrays is presented.
Then, the fitness function and the results with their discussion are presented in section 4. Finally, the paper is
concluded in section 5.
2. THE PROPOSED HYBRID OPTIMIZATION ALGORITHM
2.1. The theory of the hybrid method
In [20-22], we proposed a new hybrid method that combines the features of two metaheuristic
algorithms; Grasshopper Optimization Algorithm (GOA) [19] and Antlion Optimization (ALO)
algorithm [18]. ALO is robust in exploitation process, which has been proved in many papers in the literature
like [23, 24]. The social forces in grasshopper’s swarm show the strong ability in exploration process all over
the search space. So, these features give the chance to combine these two methods, GOA and ALO,
in a novel hybrid method, to make a huge enhancement on the performance of these algorithms. The benefits
of hybridization can be represented in overcoming the main disadvantages of GOA and ALO.
The full dependence on roulette wheel selection method is the main disadvantage in ALO, since it may cause;
loss of diversity, early convergence and not enough pressure to select the fittest search agents among same
fitness search agents. Whereas the main drawback of GOA exists in c parameter equation, which weakens
the exploitation process in the algorithm.
Our proposed Hybrid method can efficiently explore and exploit the whole search space to reach
the global optimal value, because of merging the features of GOA and ALO together. The hybrid method has
some factors that improve the ability of exploitation and exploration processes like: the population nature that
decreases local optima stagnation, the attraction and repulsion forces in GOA method, the roulette wheel
selection method and random walks in ALO method, choosing different samples of less and average fitness
search agents from next position’s matrix, and the modifications of c parameter in GOA method.
These factors and modifications lead to better diversity of the search agents all over the search space and high
probability for local optima stagnation avoidance. Furthermore, the intensity of search agents in the proposed
method has been reduced rapidly compared with ALO and GOA, due to the modification of c parameter and
its combination with other shrinking factors. Thus, the hybrid method guarantees the mature and fast
convergence compared with ALO and GOA [22].
The following equations have been used in our proposed algorithms [22]:
𝑋𝑖
𝑑
= 𝑐 (∑ 𝑐
𝑢𝑏 𝑑−𝑙𝑏 𝑑
2
𝑠(|𝑋𝑗
𝑑
− 𝑋𝑖
𝑑
|)𝑁
𝑗=1
𝑗≠𝑖
𝑋 𝑗 − 𝑋 𝑖
𝑑 𝑖𝑗
) (1)
where 𝑋𝑖
𝑑
defines the next position for 𝑖 𝑡ℎ
grasshopper and 𝑑 𝑡ℎ
dimension, 𝑢𝑏 𝑑 and 𝑙𝑏 𝑑 are the upper and
lower bounds in the dth
dimension, respectively, and 𝑠(𝑟) = 𝑓𝑒
−𝑟
𝑙 − 𝑒−𝑟
where f represents the intensity of
attraction force and l indicates the attractive length scale [22].
𝑖𝑓 𝑙 ≤ (𝐿)/2
𝑐 = 𝑐𝑚𝑎𝑥 − 𝑙
𝑐𝑚𝑎𝑥−𝑐𝑚𝑖𝑛
(
𝐿
2
)
(2)
𝑖𝑓 𝑙 >
𝐿
2
𝑐 = (𝐿 − 𝑙 + 1) × (
𝑐𝑚𝑖𝑛
𝐿×10 𝑙) (3)
where 𝑐𝑚𝑎𝑥 and 𝑐𝑚𝑖𝑛 are the maximum and minimum values, respectively, L indicates the maximum
number of iterations, and l is the current iteration [19].
𝑐 𝑡
=
𝐶 𝑡
𝐼
(4)
𝑑 𝑡
=
𝑑 𝑡
𝐼
(5)
3. Int J Elec & Comp Eng ISSN: 2088-8708
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1479
where 𝑐 𝑡
and 𝑑 𝑡
indicate the minimum and maximum of all variables at tth
iteration, respectively, and 𝐼
represents a ratio, such that 𝐼 = 10 𝑤 𝑡
𝑇
where t represents the current iteration, T indicates the maximum
number of iterations, and w is a constant that depends on the current iteration [18].
2.2. Flowchart of the hybrid algorithm [16]
In Figure 1 show the flowchart of the hybrid algorithm [16].
Figure 1. Flowchart of the hybrid algorithm
3. GEOMETRY AND PROBLEM FORMULATION
In scanned array antennas, the major lobe is steered to a specific direction, which can be applied in
wide applications like mobile and cellular communications. To accomplish this, a progressive phase shift is
added in the feeding currents [25]. Hence, the array factor equation for N-element scanned antenna array that
lies along the x-axis, with λ/2 spacing between adjacent elements, can be written as follows [25]:
𝐴𝐹(𝜑) = ∑ 𝐼 𝑛exp(𝑗𝜋(𝑛 − 1)[cos(𝜑) − cos(𝜑 𝑑)])𝑁
𝑛=1 (6)
where 𝐼 𝑛 represents the excitation amplitude of the nth
element. 𝜑 𝑑 is the angle at which the major lobe is
steered. The geometry of such a scanned array with N elements is shown in Figure 2.
Figure 2. Geometry of N-element linear array
The main objective in this paper is to minimize the maximum side lobe level (SLL) with respect to
the main lobe. With the purpose of accomplishing this goal, the following fitness function is minimized [24]:
𝑓𝑖𝑡𝑛𝑒𝑠𝑠 = max {20 log10 |
𝐴𝐹(𝜑)
𝐴𝐹(𝜑 𝑑)
|} (7)
subject to 𝜑 Î[0, 𝜑𝑠] (8)
where 𝜑 𝑑 is the angle in the direction of the major beam. [0, 𝜑𝑠] represents the side lobes region that depends
on the total number of the elements.
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4. RESULTS AND ANALYSIS
In this paper, three different examples are considered; 20-element LAA with 𝜑 𝑑 = 30°
, 26-element
LAA with 𝜑 𝑑 = 45°
and 30-element LAA with 𝜑 𝑑 = 60°
. In all the examples, the excitation currents are
optimized to minimize the side lobe level using ALO and the proposed hybrid algorithm compared to
Symbiotic Organisms Search (SOS) algorithm [25] and Firefly Algorithm (FA) [8] results. 40 search agents
and 1000 iterations are used in all examples.
4.1. Example 1: Optimization of 20-Element LAA (𝛗 𝐝 = 𝟑𝟎°
)
In this example, the excitation currents for 20-element LAA with 𝜑 𝑑 = 30°
have been optimized.
Table 1 shows the optimal values for the feeding current amplitudes and the maximum SLL for ALO,
the hybrid method, Symbiotic Organisms Search (SOS) [25] and Firefly Algorithm (FA) [8]. The maximum
SLL values in (dB) are -15.45, -15.66, -15.64 and -15.59, respectively, for ALO, the hybrid method, SOS and
FA techniques. Furthermore, the FNBW values are 29.56°, 29.44°, 29.44° and 30.08° for ALO, the hybrid,
SOS and FA, respectively, and these are almost equal. The obtained radiation patterns and convergence
curves for the proposed algorithms are displayed in Figure 3 and Figure 4. The statistical results for ALO and
the hybrid method are tabulated in Table 2. It can be noticed that the standard deviation (STD) for both
methods outperforms the STD for SOS and FA [25], which proves the stability and robustness of
the proposed methods.
Table 1. Optimum currents for 30° scanned LAA with 20 elements using ALO
and the hybrid algorithm compared to other optimization techniques
𝜑 𝑑= 30°
, N=20 Feeding current amplitudes (𝐼1 … 𝐼20) Max. SLL (dB) FNBW (degree)
ALO [1.0000, 0.48938, 0.583, 0.43543, 0.25664, 0.8691, 0.48552,
0.80474, 0.3192, 0.69249, 0.5965, 0.81911, 0.7401, 0.46723,
0.25881, 0.79585, 0.5334, 0.23493, 0.57805, 0.99917]
-15.45 29.56
Hybrid [0.86058, 0.39071, 0.31623, 0.47141, 0.36107, 0.42318,
0.59255, 0.52504, 0.43337, 0.39471, 0.64721, 0.61082, 0.49428,
0.40356, 0.45944, 0.47877, 0.3173, 0.41312, 0.22736, 1.0000]
-15.66 44.22
SOS [25] [1.0000, 0.2762, 0.4499, 0.3040, 0.3787, 0.6113, 0.5305, 0.5042,
0.5554, 0.6113, 0.4950, 0.4909, 0.5940, 0.4393, 0.3429, 0.5587,
0.4266, 0.3142, 0.4099, 0.9092]
−15.64 44.22
FA [8] [0.98041, 0.76626, 0.36907, 0.55297, 0.90715, 0.20192,
0.51964, 0.84496, 0.50948, 0.98057, 0.51426, 0.53871, 0.80273,
0.55406, 0.88082, 0.40378, 0.33214, 0.46556, 0.50348, 0.94604]
−15.59 80.03
Table 2. Performance of ALO and the hybrid algorithm for 20 independent runs
ALO Hybrid
Min value (dB) -15.4466 -15.6623
Max value (dB) -15.1441 -15.4003
Median (dB) -15.3217 -15.5586
Mean (dB) -15.3087 -15.5624
STD (dB) 0.0859 0.0674
Figure 3. Radiation patterns of ALO and the hybrid
technique for 20-element scanned LAA
Figure 4. Convergence curves for the best result of
scanned LAA using ALO and the hybrid algorithm
0 200 400 600 800 1000
-16
-14
-12
-10
-8
-6
-4
-2
0
Iteration
Bestfitnessvalue
ALO
Hybrid
5. Int J Elec & Comp Eng ISSN: 2088-8708
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1481
4.2. Example 2: Optimization of 26-Element LAA (𝛗 𝐝 = 𝟒𝟓°
)
The optimum currents values and maximum SLL for 26-element 45°
scanned array antenna are
tabulated in Table 3, while Table 4 shows the statistical properties for ALO and the hybrid method in 20
independent runs. Figure 5 and Figure 6 demonstrate the radiation patterns and convergence curves,
respectively. It is obvious that the maximum SLL value obtained using the hybrid algorithm is slightly better
than the ALO, SOS and FA techniques. For all methods, the FNBW=12.62.
Table 3. Optimum currents for 45° scanned LAA with 26-element array using ALO
and the hybrid method compared to other optimization techniques
𝜑 𝑑= 45°
, N=26 Feeding current amplitudes (𝐼1 … 𝐼26) Max. SLL (dB)
ALO [0.9845, 0.92464, 0.010525, 0.6751, 0.62702, 0.063028, 0.65201, 0.54108,
0.5882, 0.75892, 0.49313, 0.69067, 0.82217, 0.44326, 0.56542, 0.62967, 0.65334,
0.53038, 0.4111, 0.7564, 0.37021, 0.74546, 0.0055742, 0.74332, 0.36553, 1.0000]
-16.05
Hybrid [0.9777, 0.34246, 0.54211, 0.084948, 0.283, 0.52902, 0.52469, 0.40156, 0.45987,
0.58482, 0.35575, 0.5388, 0.53935, 0.58524, 0.38648, 0.63499, 0.47567, 0.50461,
0.36721, 0.45082, 0.35472, 0.3458, 0.5698, 0.23679, 0.28481, 1.0000]
-3..82
SOS [25] [1.0000, 0.2314, 0.4243, 0.4349, 0.3933, 0.4423, 0.4890, 0.3892, 0.5260, 0.5470,
0.3889, 0.8891, 0.4148, 0.5557, 0.4317, 0.7241, 0.4748, 0.3302, 0.7278, 0.5896,
0.2174, 0.5061, 0.1908, 0.4341, 0.6199, 0.9584]
−16.18
FA [8] [1, 0.72429, 0.55905, 0.44837, 0.71979, 0.31947, 0.70758, 0.62037, 0.53995,
0.86304, 0.67322, 0.71588, 0.83498, 0.77957, 0.42717, 0.79538, 0.71365,
0.63019, 0.62672, 0.6301, 0.74732, 0.060126, 0.73871, 0.59844, 0.77826, 0.9975]
−15.61
Table 4. Performance of ALO and the hybrid algorithm for 20 independent runs
ALO Hybrid
Min value (dB) -16.0487 -3..8333
Max value (dB) -15.7675 -3..3362
Median (dB) -15.8969 -3..4364
Mean (dB) -15.9033 -3..432.
STD (dB) 0.0943 0.0433
Figure 5. Radiation patterns of ALO and the hybrid
technique for 26 elements scanned LAA
Figure 6. Convergence curves for the best result of
scanned LAA using ALO and the hybrid algorithm
4.3. Example 3: Optimization of 30-Element LAA (𝛗 𝐝 = 𝟔𝟎°
)
The excitation currents for 30 elements in 60°
scanned antenna array have been investigated in this
example. Table 5 shows the best value of the maximum SLL and FNBW values for ALO, the hybrid method,
SOS and FA techniques. According to this table, it can be concluded that the hybrid algorithm somewhat
beats other techniques. Table 6 mentions the consistency for ALO and the hybrid algorithm. The radiation
patterns and convergence curves are illustrated in Figure 7 and Figure 8, respectively.
0 200 400 600 800 1000
-18
-16
-14
-12
-10
-8
-6
-4
-2
0
Iteration
Bestfitnessvalue
ALO
Hybrid
6. ISSN: 2088-8708
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1482
Table 5. Optimum currents for 60° scanned LAA with 30-element array using ALO
and the hybrid method compared to other optimization techniques
𝜑 𝑑= 60°
, N=30 Feeding current amplitudes (𝐼1 … 𝐼30) Max. SLL (dB) FNBW (degree)
ALO [0.9380, 0.5472, 0.4980, 0.4647, 0.4777, 0.0382, 0.4824, 0.7979, 0.3462,
0.4455, 0.6926, 0.3170, 0.6597, 0.6022, 0.7500, 0.1379, 0.8532, 0.5132,
0.7009, 0.1911, 0.7336, 0.7231, 0.0303, 0.6409, 0.5290, 0.3575, 0.3012,
0.2129, 0.7843, 1.0000]
-15.94 4
Hybrid [0.76681, 0.31841, 0.2907, 0.33733, 0.20298, 0.30963, 0.25103, 0.4666,
0.33325, 0.28434, 0.2275, 0.55575, 0.41659, 0.41468, 0.35724, 0.48412,
0.41547, 0.27134, 0.29311, 0.47269, 0.52282, 0.29816, 0.28305, 0.35377,
0.32292, 0.23532, 0.34489, 0.14076, 0.23816, 1.0000]
-16.20 3.4.
SOS [25] [1.0000 0.9219 0.4011 0.1512 0.6258 0.0149 0.7433 0.5357 0.4412
0.8182 0.3055 0.5388 0.8813 0.5962 0.4734 0.8110 0.3965 0.6665 0.3149
0.7865 0.6591 0.4047 0.3755 0.5224 0.5257 0.5935 0.2734 0.3698
0.6766 0.9982]
−15.93 4
FA [8] [0.99575, 0.68442, 0.62997, 0.049937, 0.17937, 0.73457, 0.48525,
0.61814, 0.33365, 0.63189, 0.63643, 0.39343, 0.49183, 0.77247, 0.64547,
0.48407, 0.73964, 0.74411, 0.52797, 0.45014, 0.82218, 0.52901, 0.45825,
0.41905, 0.48686, 0.24166, 0.86684, 0.63618, 0.29691, 0.99934]
−15.97 4.03
Table 6. Performance of ALO and the hybrid algorithm for 20 independent runs
ALO Hybrid
Min value (dB) -15.9449 -3..3464
Max value (dB) -15.6637 -36.4.36
Median value (dB) -15.8149 -3..0668
Mean value (dB) -15.8074 -3..0344
STD (dB) 0.0865 0.0603
Figure 7. Radiation patterns of ALO and the hybrid
technique for 30-element array scanned LAA
Figure 8. Convergence curves for the best result of
scanned LAA using ALO and the hybrid algorith
5. CONCLUSION
In this paper, optimal design of scanned linear antenna arrays was performed using two
metaheuristic algorithms; Antlion optimization (ALO) algorithm and our new proposed hybrid algorithm
based on Grasshopper Optimization algorithm (GOA) and ALO. Our objective function in this paper was to
reduce the side lobe level with the constraint of a fixed major lobe beamwidth. In this paper, three examples
were discussed; 20-element, 26-element and 30-element scanned antenna array. The results show that
the proposed hybrid algorithm is very competitive in reducing the SLL compared to other methods like;
SOS and FA. In all experiments, a population size of 40 and 200 iterations only were enough to
reach to the solution.
7. Int J Elec & Comp Eng ISSN: 2088-8708
The optimal synthesis of scanned linear antenna arrays (Anas A Amaireh)
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BIOGRAPHIES OF AUTHORS
Anas Atef Amaireh received his B.Sc. and M.Sc. degrees in Engineering Technology with
the major of Wireless Communication Engineering from Yarmouk University, Jordan in 2015 and
2018, respectively. His research interests are in antenna arrays, numerical techniques in
electromagnetics, stochastic algorithms and optimization techniques.
8. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1477 - 1484
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Asem S. Al-Zoubi received his B.Sc. degree in Electrical Engineering from Eastern Mediterranean
University, Cyprus in 1993, the M.Sc. degree in Electrical Engineering from Jordan University of
Science and Technology, Jordan in 1998, and the Ph.D. degree in Electrical Engineering/
Electromagnetics from the University of Mississippi, USA, in 2008. Currently, he is an
Associate Professor with the Department of Telecommunications Engineering in Yarmouk
University, Jordan. His current research interests include dielectric resonator antennas, microstrip
antennas, and numerical techniques in electromagnetics. Mr. Al-Zoubi is a member of the IEEE
Nihad I. Dib obtained his B. Sc. and M.Sc. in Electrical Engineering from Kuwait University in
1985 and 1987, respectively. He obtained his Ph.D. in EE (major in Electromagnetics) in 1992 from
University of Michigan, Ann Arbor. Then, he worked as an assistant research scientist in
the radiation laboratory at the same school. In Sep. 1995, he joined the EE department at Jordan
University of Science and Technology (JUST) as an assistant professor, and became a full professor
in Aug. 2006. His research interests are in computational electromagnetics, antennas and modeling
of planar microwave circuits