This document presents a Particle Swarm Optimization (PSO) based PID controller for a bidirectional inductive power transfer system. PSO is used to optimize the parameters of a PID controller (proportional, integral and derivative terms) to minimize error and improve system performance. The proposed PSO-tuned PID controller is simulated and its performance is compared to other tuning methods. Results demonstrate the validity and effectiveness of using PSO to optimize PID control parameters for bidirectional power transfer systems.
Stability analysis and design of algorithmic tuned pid controller for bio rea...eSAT Journals
Abstract The paper proposes a detailed analysis of various intelligent algorithms for the application of tuning PID controllers for time delayed model with a specific stability analysis on the unstable phase of a Bio- reactor system. The tuning process is focused mainly to search the optimal controller parameters (Kp, Ki, Kd) by minimizing the performance criterion and with the help of the objective function. Relative studies on various cost functions like integral of squared error (ISE), integral of absolute error (IAE), integrated time squared error (ITSE), integrated time absolute error (ITAE) have also been performed for the tuned system. The stability analysis for the algorithmic tuned PID controller by Nyquist plot is also performed for the various working phases of the considered bio reactor model. The simulation results show that the proposed tuning approach provides superior results such as smooth set point tracking, error minimization and increased stable response. Keywords: stability, PID, PSO, BFO, FF, bio reactor
Design and optimization of pid controller using genetic algorithmeSAT Journals
Abstract Natural evolution is mimicked by Genetic Algorithms (GAs) which is a stochastic global search method used for optimization. . In missile control systems Proportional Integral Derivative (PID) control is widely used, but due to empirically selected parameters Kp, Ki, Kd it is difficult to achieve parameter optimization. Genetic algorithm is a search algorithm that is based on natural selection and genetics principles.GA is a computational algorithm which deals with genetics of the human body. It evolves with the number of iterations. After ever iteration a better result is expected. These results are checked for the error. The fittest roots or solution are considered for the next generation based on the selection criterion. GA randomly generates the initial population of the PID control parameters according to the calculation of selection (Normalized Geometric Selection), crossover (Arithmetic Crossover) and mutation (Uniform Mutation), thus optimizing the control parameters. Mean Square Error (MSE) value is chosen as the performance assessment index. For a missile altitude control Proportional Integral Derivative (PID) controller using genetic algorithm is implemented & compared with the classical method Zeigler-Nichols (Z-N) in the paper. Z-N method is classical method which tunes the parameters of PID. The parameters of PID are difficult to tune. Tuned parameters give the optimum solution. Optimum solution generally converges to a solution having minimum error. Minimum error gives a response of the system in terms of maximum over shoot, Settling time, Rise time & Steady State Error. The designed PID with the Genetic Algorithm has much faster response than the classical method.
Stability analysis and design of algorithmic tuned pid controller for bio rea...eSAT Journals
Abstract The paper proposes a detailed analysis of various intelligent algorithms for the application of tuning PID controllers for time delayed model with a specific stability analysis on the unstable phase of a Bio- reactor system. The tuning process is focused mainly to search the optimal controller parameters (Kp, Ki, Kd) by minimizing the performance criterion and with the help of the objective function. Relative studies on various cost functions like integral of squared error (ISE), integral of absolute error (IAE), integrated time squared error (ITSE), integrated time absolute error (ITAE) have also been performed for the tuned system. The stability analysis for the algorithmic tuned PID controller by Nyquist plot is also performed for the various working phases of the considered bio reactor model. The simulation results show that the proposed tuning approach provides superior results such as smooth set point tracking, error minimization and increased stable response. Keywords: stability, PID, PSO, BFO, FF, bio reactor
Design and optimization of pid controller using genetic algorithmeSAT Journals
Abstract Natural evolution is mimicked by Genetic Algorithms (GAs) which is a stochastic global search method used for optimization. . In missile control systems Proportional Integral Derivative (PID) control is widely used, but due to empirically selected parameters Kp, Ki, Kd it is difficult to achieve parameter optimization. Genetic algorithm is a search algorithm that is based on natural selection and genetics principles.GA is a computational algorithm which deals with genetics of the human body. It evolves with the number of iterations. After ever iteration a better result is expected. These results are checked for the error. The fittest roots or solution are considered for the next generation based on the selection criterion. GA randomly generates the initial population of the PID control parameters according to the calculation of selection (Normalized Geometric Selection), crossover (Arithmetic Crossover) and mutation (Uniform Mutation), thus optimizing the control parameters. Mean Square Error (MSE) value is chosen as the performance assessment index. For a missile altitude control Proportional Integral Derivative (PID) controller using genetic algorithm is implemented & compared with the classical method Zeigler-Nichols (Z-N) in the paper. Z-N method is classical method which tunes the parameters of PID. The parameters of PID are difficult to tune. Tuned parameters give the optimum solution. Optimum solution generally converges to a solution having minimum error. Minimum error gives a response of the system in terms of maximum over shoot, Settling time, Rise time & Steady State Error. The designed PID with the Genetic Algorithm has much faster response than the classical method.
PSO APPLIED TO DESIGN OPTIMAL PD CONTROL FOR A UNICYCLE MOBILE ROBOTJaresJournal
In this work, we propose a Particle Swarm Optimization (PSO) to design Proportional Derivative
controllers (PD) for the control of Unicycle Mobile Robot. To stabilize and drive the robot precisely with
the predefined trajectory, a decentralized control structure is adopted where four PD controllers are used.
Their parameters are given simultaneously by the proposed algorithm (PSO). The performance of the
system from its desired behavior is quantified by an objective function (SE). Simulation results are
presented to show the efficiency of the method. ).
The results are very conclusive and satisfactory in terms of stability and trajectory tracking of unicycle
mobile robot
A Heuristic Approach for optimization of Non Linear process using Firefly Alg...IJERA Editor
A comparison study of Firefly Algorithm (FA) and Bacterial Foraging Algorithm (BFO) optimization is carried out by applying them to a Non Linear pH neutralization process. In process control engineering, the Proportional, Derivative, Integral controller tuning parameters are deciding the performance of the controller to ensure the good performance of the plant. The FA and BFO algorithms are applied to obtain the optimum values of controller parameters. The performance indicators such as servo response and regulatory response tests are carried out to evaluate the efficiency of the heuristic algorithm based controllers. The error minimization criterion such as Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Square Error (ITSE), Integral Time Absolute Error (ITAE) and Time domain specifications – rise time, Peak Overshoot and settling time are considered for the study of the performance of the controllers. The study indicates that, FA tuned PID controller provides marginally better set point tracking, load disturbance rejection, time domain specifications and error minimization for the Non Linear pH neutralization process compared to BFO tuned PID controller.
The modern power system around the world has grown in complexity of interconnection and
power demand. The focus has shifted towards enhanced performance, increased customer focus,
low cost, reliable and clean power. In this changed perspective, scarcity of energy resources,
increasing power generation cost, environmental concern necessitates optimal economic dispatch.
In reality power stations neither are at equal distances from load nor have similar fuel cost
functions. Hence for providing cheaper power, load has to be distributed among various power
stations in a way which results in lowest cost for generation. Practical economic dispatch (ED)
problems have highly non-linear objective function with rigid equality and inequality constraints.
Particle swarm optimization (PSO) is applied to allot the active power among the generating
stations satisfying the system constraints and minimizing the cost of power generated. The
viability of the method is analyzed for its accuracy and rate of convergence. The economic load
dispatch problem is solved for three and six unit system using PSO and conventional method for
both cases of neglecting and including transmission losses. The results of PSO method were
compared with conventional method and were found to be superior. The conventional
optimization methods are unable to solve such problems due to local optimum solution
convergence. Particle Swarm Optimization (PSO) since its initiation in the last 15 years has been
a potential solution to the practical constrained economic load dispatch (ELD) problem. The
optimization technique is constantly evolving to provide better and faster results.
While writing the report on our project seminar, we were wondering that Science and smart
technology are as ever expanding field and the engineers working hard day and night and make
the life a gift for us
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Presenting a new Ant Colony Optimization Algorithm (ACO) for Efficient Job Sc...Editor IJCATR
Grid computing utilizes the distributed heterogeneous resources in order to support complicated computing problems. Job
scheduling in computing grid is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign
jobs to resources in grids.
In the natural environment, the ants have a tremendous ability to team up to find an optimal path to food resources. An ant algorithm
simulates the behavior of ants. In this paper, a new Ant Colony Optimization (ACO) algorithm is proposed for job scheduling in the
Grid environment. The main contribution of this paper is to minimize the makespan of a given set of jobs. Compared with the other job
scheduling algorithms, the proposed algorithm can outperform them according to the experimental results.
An Application of Genetic Programming for Power System Planning and OperationIDES Editor
This work incorporates the identification of model
in functional form using curve fitting and genetic programming
technique which can forecast present and future load
requirement. Approximating an unknown function with
sample data is an important practical problem. In order to
forecast an unknown function using a finite set of sample
data, a function is constructed to fit sample data points. This
process is called curve fitting. There are several methods of
curve fitting. Interpolation is a special case of curve fitting
where an exact fit of the existing data points is expected.
Once a model is generated, acceptability of the model must be
tested. There are several measures to test the goodness of a
model. Sum of absolute difference, mean absolute error, mean
absolute percentage error, sum of squares due to error (SSE),
mean squared error and root mean squared errors can be used
to evaluate models. Minimizing the squares of vertical distance
of the points in a curve (SSE) is one of the most widely used
method .Two of the methods has been presented namely Curve
fitting technique & Genetic Programming and they have been
compared based on (SSE)sum of squares due to error.
Voltage Stability Improvement by Reactive Power Rescheduling Incorporating P...IJMER
In this paper, reactive power rescheduling is done to keep the voltage stable. Due to system
disturbances the active as well as reactive power flows changes. Generators being always connected to the
system reactive power rescheduling of generators can be effectively done. Therefore it is selected as the
suitable method for voltage control. The voltage and reactive power management is studied from the
generator’s point of view to minimize generator reactive power loss. To reduce the reactive losses
optimization procedure is used. The simulations are done using MATLAB.
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.
Rainfall prediction is a major problem in metrological department and it is closely
associated with the economy and life of human. Accuracy of rainfall prediction is a
very important for countries like india, because Indian economy is mainly dependent
up on the agriculture. Most of the statistical methods are unsuccessful due to dynamic
nature of atmosphere. In this paper, SVM classifier is used for classification, before
SVM classifier, bees algorithm is used for feature selection. Keeping all the features
and instances in the training set is not a good approach for better classification
because all the features are not contributing more information during classification,
removing those features will not affect any classification accuracy. The experimental
result shows that the proposed method provides better detection rate, false positive
Proposing a scheduling algorithm to balance the time and cost using a genetic...Editor IJCATR
Grid computing is a hardware and software infrastructure and provides affordable, sustainable, and reliable access. Its aim is
to create a supercomputer using free resources. One of the challenges to the Grid computing is scheduling problem which is regarded
as a tough issue. Since scheduling problem is a non-deterministic issue in the Grid, deterministic algorithms cannot be used to improve
scheduling.
In this paper, a combination of genetic algorithms and binary gravitational attraction is used for scheduling problem solving, where the
reduction in the duty performance timing and cost-effective use of simultaneous resources are investigated. In this case, the user
determines the execution time parameter and cost-effective use of resources. In this algorithm, a new approach that has led to a
balanced load of resources is used in the selection of resources. Experimental results reveals that our proposed algorithm in terms of
cost-time and selection of the best resource has reached better results than other algorithm.
How to optimize with the help of the Particle Swarm Optimization Technique and xlOptimizer ? This brief tutorial will enable you to solve any optimization problem with the application of Particle Swarm Optimization Method. After a brief introduction about the method the tutorial will show you the steps that you will need to follow for application of PSO in optimization even if you do not know any programming.(Some basic knowledge of MS Excel 2010 and later is required).
In the present work, Lyapunov stability theory, nonlinear adaptive control law and the parameter update
law were utilized to derive the state of two new chaotic reversal systems after being synchronized by the
function projective method. Using this technique allows for a scaling function instead of a constant thereby
giving a better method in applications in secure communication. Numerical simulations are presented to
demonstrate the effective nature of the proposed scheme of synchronization for the new chaotic reversal
system.
Feature selection using modified particle swarm optimisation for face recogni...eSAT Journals
Abstract
One of the major influential factors which affects the accuracy of classification rate is the selection of right features. Not all features have vital role in classification. Many of the features in the dataset may be redundant and irrelevant, which increase the computational cost and may reduce classification rate. In this paper, we used DCT(Discrete cosine transform) coefficients as features for face recognition application. The coefficients are optimally selected based on a modified PSO algorithm. In this, the choice of coefficients is done by incorporating the average of the mean normalized standard deviations of various classes and giving more weightage to the lower indexed DCT coefficients. The algorithm is tested on ORL database. A recognition rate of 97% is obtained. Average number of features selected is about 40 percent for a 10 × 10 input. The modified PSO took about 50 iterations for convergence. These performance figures are found to be better than some of the work reported in literature.
Keywords: Particle swarm optimization, Discrete cosine transform, feature extraction, feature selection, face recognition, classification rate.
PSO APPLIED TO DESIGN OPTIMAL PD CONTROL FOR A UNICYCLE MOBILE ROBOTJaresJournal
In this work, we propose a Particle Swarm Optimization (PSO) to design Proportional Derivative
controllers (PD) for the control of Unicycle Mobile Robot. To stabilize and drive the robot precisely with
the predefined trajectory, a decentralized control structure is adopted where four PD controllers are used.
Their parameters are given simultaneously by the proposed algorithm (PSO). The performance of the
system from its desired behavior is quantified by an objective function (SE). Simulation results are
presented to show the efficiency of the method. ).
The results are very conclusive and satisfactory in terms of stability and trajectory tracking of unicycle
mobile robot
A Heuristic Approach for optimization of Non Linear process using Firefly Alg...IJERA Editor
A comparison study of Firefly Algorithm (FA) and Bacterial Foraging Algorithm (BFO) optimization is carried out by applying them to a Non Linear pH neutralization process. In process control engineering, the Proportional, Derivative, Integral controller tuning parameters are deciding the performance of the controller to ensure the good performance of the plant. The FA and BFO algorithms are applied to obtain the optimum values of controller parameters. The performance indicators such as servo response and regulatory response tests are carried out to evaluate the efficiency of the heuristic algorithm based controllers. The error minimization criterion such as Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Square Error (ITSE), Integral Time Absolute Error (ITAE) and Time domain specifications – rise time, Peak Overshoot and settling time are considered for the study of the performance of the controllers. The study indicates that, FA tuned PID controller provides marginally better set point tracking, load disturbance rejection, time domain specifications and error minimization for the Non Linear pH neutralization process compared to BFO tuned PID controller.
The modern power system around the world has grown in complexity of interconnection and
power demand. The focus has shifted towards enhanced performance, increased customer focus,
low cost, reliable and clean power. In this changed perspective, scarcity of energy resources,
increasing power generation cost, environmental concern necessitates optimal economic dispatch.
In reality power stations neither are at equal distances from load nor have similar fuel cost
functions. Hence for providing cheaper power, load has to be distributed among various power
stations in a way which results in lowest cost for generation. Practical economic dispatch (ED)
problems have highly non-linear objective function with rigid equality and inequality constraints.
Particle swarm optimization (PSO) is applied to allot the active power among the generating
stations satisfying the system constraints and minimizing the cost of power generated. The
viability of the method is analyzed for its accuracy and rate of convergence. The economic load
dispatch problem is solved for three and six unit system using PSO and conventional method for
both cases of neglecting and including transmission losses. The results of PSO method were
compared with conventional method and were found to be superior. The conventional
optimization methods are unable to solve such problems due to local optimum solution
convergence. Particle Swarm Optimization (PSO) since its initiation in the last 15 years has been
a potential solution to the practical constrained economic load dispatch (ELD) problem. The
optimization technique is constantly evolving to provide better and faster results.
While writing the report on our project seminar, we were wondering that Science and smart
technology are as ever expanding field and the engineers working hard day and night and make
the life a gift for us
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Presenting a new Ant Colony Optimization Algorithm (ACO) for Efficient Job Sc...Editor IJCATR
Grid computing utilizes the distributed heterogeneous resources in order to support complicated computing problems. Job
scheduling in computing grid is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign
jobs to resources in grids.
In the natural environment, the ants have a tremendous ability to team up to find an optimal path to food resources. An ant algorithm
simulates the behavior of ants. In this paper, a new Ant Colony Optimization (ACO) algorithm is proposed for job scheduling in the
Grid environment. The main contribution of this paper is to minimize the makespan of a given set of jobs. Compared with the other job
scheduling algorithms, the proposed algorithm can outperform them according to the experimental results.
An Application of Genetic Programming for Power System Planning and OperationIDES Editor
This work incorporates the identification of model
in functional form using curve fitting and genetic programming
technique which can forecast present and future load
requirement. Approximating an unknown function with
sample data is an important practical problem. In order to
forecast an unknown function using a finite set of sample
data, a function is constructed to fit sample data points. This
process is called curve fitting. There are several methods of
curve fitting. Interpolation is a special case of curve fitting
where an exact fit of the existing data points is expected.
Once a model is generated, acceptability of the model must be
tested. There are several measures to test the goodness of a
model. Sum of absolute difference, mean absolute error, mean
absolute percentage error, sum of squares due to error (SSE),
mean squared error and root mean squared errors can be used
to evaluate models. Minimizing the squares of vertical distance
of the points in a curve (SSE) is one of the most widely used
method .Two of the methods has been presented namely Curve
fitting technique & Genetic Programming and they have been
compared based on (SSE)sum of squares due to error.
Voltage Stability Improvement by Reactive Power Rescheduling Incorporating P...IJMER
In this paper, reactive power rescheduling is done to keep the voltage stable. Due to system
disturbances the active as well as reactive power flows changes. Generators being always connected to the
system reactive power rescheduling of generators can be effectively done. Therefore it is selected as the
suitable method for voltage control. The voltage and reactive power management is studied from the
generator’s point of view to minimize generator reactive power loss. To reduce the reactive losses
optimization procedure is used. The simulations are done using MATLAB.
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.
Rainfall prediction is a major problem in metrological department and it is closely
associated with the economy and life of human. Accuracy of rainfall prediction is a
very important for countries like india, because Indian economy is mainly dependent
up on the agriculture. Most of the statistical methods are unsuccessful due to dynamic
nature of atmosphere. In this paper, SVM classifier is used for classification, before
SVM classifier, bees algorithm is used for feature selection. Keeping all the features
and instances in the training set is not a good approach for better classification
because all the features are not contributing more information during classification,
removing those features will not affect any classification accuracy. The experimental
result shows that the proposed method provides better detection rate, false positive
Proposing a scheduling algorithm to balance the time and cost using a genetic...Editor IJCATR
Grid computing is a hardware and software infrastructure and provides affordable, sustainable, and reliable access. Its aim is
to create a supercomputer using free resources. One of the challenges to the Grid computing is scheduling problem which is regarded
as a tough issue. Since scheduling problem is a non-deterministic issue in the Grid, deterministic algorithms cannot be used to improve
scheduling.
In this paper, a combination of genetic algorithms and binary gravitational attraction is used for scheduling problem solving, where the
reduction in the duty performance timing and cost-effective use of simultaneous resources are investigated. In this case, the user
determines the execution time parameter and cost-effective use of resources. In this algorithm, a new approach that has led to a
balanced load of resources is used in the selection of resources. Experimental results reveals that our proposed algorithm in terms of
cost-time and selection of the best resource has reached better results than other algorithm.
How to optimize with the help of the Particle Swarm Optimization Technique and xlOptimizer ? This brief tutorial will enable you to solve any optimization problem with the application of Particle Swarm Optimization Method. After a brief introduction about the method the tutorial will show you the steps that you will need to follow for application of PSO in optimization even if you do not know any programming.(Some basic knowledge of MS Excel 2010 and later is required).
In the present work, Lyapunov stability theory, nonlinear adaptive control law and the parameter update
law were utilized to derive the state of two new chaotic reversal systems after being synchronized by the
function projective method. Using this technique allows for a scaling function instead of a constant thereby
giving a better method in applications in secure communication. Numerical simulations are presented to
demonstrate the effective nature of the proposed scheme of synchronization for the new chaotic reversal
system.
Feature selection using modified particle swarm optimisation for face recogni...eSAT Journals
Abstract
One of the major influential factors which affects the accuracy of classification rate is the selection of right features. Not all features have vital role in classification. Many of the features in the dataset may be redundant and irrelevant, which increase the computational cost and may reduce classification rate. In this paper, we used DCT(Discrete cosine transform) coefficients as features for face recognition application. The coefficients are optimally selected based on a modified PSO algorithm. In this, the choice of coefficients is done by incorporating the average of the mean normalized standard deviations of various classes and giving more weightage to the lower indexed DCT coefficients. The algorithm is tested on ORL database. A recognition rate of 97% is obtained. Average number of features selected is about 40 percent for a 10 × 10 input. The modified PSO took about 50 iterations for convergence. These performance figures are found to be better than some of the work reported in literature.
Keywords: Particle swarm optimization, Discrete cosine transform, feature extraction, feature selection, face recognition, classification rate.
Optimization of automatic voltage regulator by proportional integral derivati...eSAT Journals
Abstract
This paper is basically based on the optimization of working of Automatic voltage regulator by the proportional Intigral
derivative controller. In this analysis, optimization is done by very novel concept Particle Swarm Optimization and simulated
using MATLAB Simulink software. The primary reason for a programmed voltage controller framework is to keep the voltage
extent of a synchronous generator at a predetermined level the generator excitation framework keeps up the generator voltage
and controls the reactive power stream.
IndexTerms:AutomaticVoltageRegulator,MATLAB
Software Effort Estimation Using Particle Swarm Optimization with Inertia WeightWaqas Tariq
Software is the most expensive element of virtually all computer based systems. For complex custom systems, a large effort estimation error can make the difference between profit and loss. Cost (Effort) Overruns can be disastrous for the developer. The basic input for the effort estimation is size of project. A number of models have been proposed to construct a relation between software size and Effort; however we still have problems for effort estimation because of uncertainty existing in the input information. Accurate software effort estimation is a challenge in Industry. In this paper we are proposing three software effort estimation models by using soft computing techniques: Particle Swarm Optimization with inertia weight for tuning effort parameters. The performance of the developed models was tested by NASA software project dataset. The developed models were able to provide good estimation capabilities.
Application of optimization algorithms for classification problemIJECEIAES
The work presented in this paper investigates the use of metaheuristic optimization algorithms for the face recognition problem. In the first setup, a face recognition system is implemented using particle swarm optimization (PSO) and firefly optimization algorithms, separately. PSO and firefly are used for forming the feature vectors in the feature selection stage. These feature vectors serve as the new representation for the face images that will be fed to the classifier. In the second setup, selected features from both PSO and firefly algorithms are fused to form one single feature vector for each face image before the classification stage. Extensive simulations are conducted using Poznan University of Technology (PUT) and face recognition technology (FERET) face databases. Optimal values for population size and maximum iterations number were selected before conducting the experiments. The effect of using different numbers of selected features on the performance is investigated for feature selection using PSO, firefly, and feature fusion of both.
Optimization of FLC Using PSO – FF Hybrid Algorithm Using DSTATCOM for Powe...YogeshIJTSRD
Electrical power is the most established form of power and the people is greatly dependant on the electric power supply. A life cannot be imagined with no supply of electricity. Most of the industrial and domestic loads require uninterrupted and high standard continuous power supply. The electric power suppliers and consumers are getting more concerned about the quality of electric power that is provided to them and which is consumed by the users. Therefore, retaining the qualitative power is of most important 1 . In this research paper our main aim is to optimize and Analysed the performance of PSO – FF hybrid algorithms 2 for the control of DSTATCOM in power quality improvement 3 and the results are analysed with the help of MATLAB software. Kamal Kumar | Poonam Kumari "Optimization of FLC Using PSO – FF Hybrid Algorithm Using DSTATCOM for Power Quality Improvement" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd44962.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/44962/optimization-of-flc-using-pso- – -ff-hybrid-algorithm-using-dstatcom-for-power-quality-improvement/kamal-kumar
A REVIEW OF PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHMIAEME Publication
Particle swarm optimization (PSO) is a population-based stochastic optimization technique that is inspired by the intelligent collective behaviour of certain animals, such as flocks of birds or schools of fish. It has undergone numerous improvements since its debut in 1995. As academics became more familiar with the technique, they produced additional versions aimed at different demands, created new applications in a variety of fields, published theoretical analyses of the impacts of various factors, and offered other variants of the algorithm. This paper discusses the PSO's origins and background, as well as its theory analysis. Then, we examine the current state of research and application in algorithm structure, parameter selection, topological structure, discrete and parallel PSO algorithms, multi-objective optimization PSO, and engineering applications. Finally, existing difficulties are discussed, and new study directions are proposed.
MPPT for Photovoltaic System Using Multi-objective Improved Particle Swarm Op...Nooria Sukmaningtyas
Making full use of abundant renewable solar energy through the development of photovoltaic (PV)
technology is an effective means to solve the problems such as difficulty in electricity supply and energy
shortages in remote rural areas. In order to improve the electricity generating efficiency of PV cells, it is
necessary to track the maximum power point of PV array, which is difficult to make under partially shaded
conditions due to the odds of the appearance of two or more local maximum power points., In this paper, a
control algorithm of maximum power point tracking (MPPT) based on improved particle swarm optimization
(IPSO) algorithm is presented for PV systems. Firstly, the current in maximum power point is searched
with the IPSO algorithm, and then the real maximum power point is tracked through controlling the output
current of PV array. The MPPT method based on IPSO algorithm is established and simulated with Matlab
/ Simulink, and meanwhile, the comparison between IPSO MPPT algorithm and traditional MPPT algorithm
is also performed in this paper. It is proved through simulation and experimental results that the IPSO
algorithm has good performances and very fast response even to partial shaded PV modules, , which
ensures the stability of PV system.
DriP PSO- A fast and inexpensive PSO for drifting problem spacesZubin Bhuyan
Particle Swarm Optimization is a class of stochastic, population based optimization techniques which are mostly suitable for static problems. However, real world optimization problems are time variant, i.e., the problem space changes over time. Several researches have been done to address this dynamic optimization problem using Particle Swarms. In this paper we probe the issues of tracking and optimizing Particle Swarms in a dynamic system where the problem-space drifts in a particular direction. Our assumption is that the approximate amount of drift is known, but the direction of the drift is unknown. We propose a Drift Predictive PSO (DriP-PSO) model which does not incur high computation cost, and is very fast and accurate. The main idea behind this technique is to use a few stagnant particles to determine the approximate direction in which the problem-space is drifting so that the particle velocities may be adjusted accordingly in the subsequent iteration of the algorithm.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
About
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.
• 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.
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.
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.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
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.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
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.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.