This document presents a multi-objective optimization method for economic emission load dispatch (EELD) that considers economy, emissions, and transmission line security as objectives. The problem is formulated to minimize total fuel costs and emissions while maximizing line security for a power system. The multi-objective problem is converted to a single objective using goal attainment and then solved using simulated annealing. Results are presented for a 30-bus and 57-bus IEEE test case system to demonstrate the proposed method.
Multi objective economic load dispatch using hybrid fuzzy, bacterialIAEME Publication
The document summarizes a research paper that proposes a new approach for solving the economic load dispatch problem using a hybrid fuzzy, bacterial foraging-Nelder–Mead algorithm. The economic load dispatch problem minimizes generation costs while satisfying load demand under system constraints. The proposed approach considers generation costs, spinning reserve costs, and emission costs simultaneously. It also accounts for valve-point effects, prohibited operating zones, and other practical constraints. A hybrid bacterial foraging and Nelder–Mead algorithm combined with fuzzy logic is used to solve the optimization problem. Simulation results show the advantages of the proposed method in reducing total system costs.
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...IJERA Editor
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
GWO-based estimation of input-output parameters of thermal power plantsTELKOMNIKA JOURNAL
This document presents a study that uses the Grey Wolf Optimizer (GWO) method to estimate the input-output parameters of the fuel cost curve for thermal power plants.
The fuel cost curve represents the relationship between a plant's fuel costs and power output, and needs to be periodically re-estimated due to temperature and aging effects. Accurately estimating the curve's parameters is important for economic dispatch calculations.
The study formulates parameter estimation as an optimization problem to minimize errors between actual and estimated fuel costs. It applies GWO to find the parameters for different fuel cost curve models using test data from three power plants. Simulation results show GWO provides better parameter estimates than other estimation methods.
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.
Compromising between-eld-&-eed-using-gatool-matlabSubhankar Sau
Creating a compromising points between economic load dispatch & emission created from the plant to minimising those effects.
these are created by using MATLAB and GATOOL .
taking Weighted Sum Method,also Pareto optimal curve.
created by: SUBHANKAR SAU
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.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
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.
Multi objective economic load dispatch using hybrid fuzzy, bacterialIAEME Publication
The document summarizes a research paper that proposes a new approach for solving the economic load dispatch problem using a hybrid fuzzy, bacterial foraging-Nelder–Mead algorithm. The economic load dispatch problem minimizes generation costs while satisfying load demand under system constraints. The proposed approach considers generation costs, spinning reserve costs, and emission costs simultaneously. It also accounts for valve-point effects, prohibited operating zones, and other practical constraints. A hybrid bacterial foraging and Nelder–Mead algorithm combined with fuzzy logic is used to solve the optimization problem. Simulation results show the advantages of the proposed method in reducing total system costs.
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...IJERA Editor
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
GWO-based estimation of input-output parameters of thermal power plantsTELKOMNIKA JOURNAL
This document presents a study that uses the Grey Wolf Optimizer (GWO) method to estimate the input-output parameters of the fuel cost curve for thermal power plants.
The fuel cost curve represents the relationship between a plant's fuel costs and power output, and needs to be periodically re-estimated due to temperature and aging effects. Accurately estimating the curve's parameters is important for economic dispatch calculations.
The study formulates parameter estimation as an optimization problem to minimize errors between actual and estimated fuel costs. It applies GWO to find the parameters for different fuel cost curve models using test data from three power plants. Simulation results show GWO provides better parameter estimates than other estimation methods.
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.
Compromising between-eld-&-eed-using-gatool-matlabSubhankar Sau
Creating a compromising points between economic load dispatch & emission created from the plant to minimising those effects.
these are created by using MATLAB and GATOOL .
taking Weighted Sum Method,also Pareto optimal curve.
created by: SUBHANKAR SAU
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.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
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.
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
This document presents an improved differential evolution algorithm for congestion management in power systems with wind turbine generators. The algorithm determines the optimal location of new wind farms based on bus sensitivity factor and wind availability factor. It then uses an enhanced differential evolution approach to reschedule generators and install new wind farms to relieve transmission line congestion. The algorithm is tested on the IEEE 30-bus system and is shown to be more effective at congestion management than other approaches.
PuShort Term Hydrothermal Scheduling using Evolutionary Programmingblished pa...Satyendra Singh
In this paper, Evolutionary Programming method
is used for short term hydrothermal scheduling which minimize
the total fuel cost while satisfying the constraints. This paper
developed and studies the performance of evolutionary programs
in solving hydrothermal scheduling problem. The effectiveness of
the developed program is tested for the system having one hydro
and one thermal unit for 24 hour load demand. Numerical results
show that highly near-optimal solutions can be obtained by
Evolutionary Programming.
The document summarizes a study on reducing CO2 emissions from thermal power plants through load dispatch scheduling. It presents equations to calculate CO2 emissions from power plants and describes using evolutionary algorithms to optimize load scheduling across three power plants. The results show evolutionary techniques achieved the lowest overall CO2 emissions of 8,426 tons compared to other methods, while maintaining the same total power output. The conclusion is that properly selecting which plants generate power through load scheduling can reduce CO2 emissions without additional equipment.
Comparisional Investigation of Load Dispatch Solutions with TLBO IJECEIAES
This paper discusses economic load dispatch Problem is modeled with nonconvex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This proposed algorithm is applied to solve the load dispatch problem for 6 unit and 10 unit test systems along with the other algorithms. This comparisional investigation explored various merits of TLBO with respect to PSO, DE, and HAS in the field economic load dispatch.
Multi-objective Optimization Scheme for PID-Controlled DC MotorIAES-IJPEDS
DC Motor is the most basic electro-mechanical equipment and well-known for its merit and simplicity. The performance of DC motor is assessed based on several qualities that are most-likely contradictory each other, i.e. settling time and overshoot percentage. Most of controller’s optimization problems are multi-objective in nature since they normally have several conflicting objectives that must be met simultaneously. In this study, the grey relational analysis (GRA) was combined with Taguchi method to search the optimum PID parameter for multi-objective problem. First, a L9 (33) orthogonal array was used to plan out the processing parameters that would affect the DC motor’s speed. Then GRA was applied to overcome the drawback of single quality characteristics in the Taguchi method, and then the optimized PID parameter combination was obtained for multiple quality characteristics from the response table and the response graph from GRA. Signal-to-noise ratio (S/N ratio) calculation and analysis of variance (ANOVA) would be performed to find out the significant factors. Lastly, the reliability and reproducibility of the experiment was verified by confirming a confidence interval (CI) of 95%.
Optimization of Economic Load Dispatch with Unit Commitment on Multi MachineIJAPEJOURNAL
Economic load dispatch (ELD) and Unit Commitment (UC) are significant research applications in power systems that optimize the total production cost of the predicted load demand. The UC problem determines a turn-on and turn-off schedule for a given combination of generating units, thus satisfying a set of dynamic operational constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the load demands of customers. The first phase in this project is to economically schedule the distribution of generating units using Gauss seidal and the second phase is to determine optimal load distribution for the scheduled units using dynamic programming method is applied to select and choose the combination of generating units that commit and de-commit during each hour. These precommitted schedules are optimized by dynamic programming method thus producing a global optimum solution with feasible and effective solution quality, minimal cost and time and higher precision. The effectiveness of the proposed techniques is investigated on two test systems consisting of five generating units and the experiments are carried out using MATLAB R2010b software. Experimental results prove that the proposed method is capable of yielding higher quality solution including mathematical simplicity, fast convergence, diversity maintenance, robustness and scalability for the complex ELD-UC problem.
Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization TechniquejournalBEEI
This document presents a study that uses Particle Swarm Optimization (PSO) technique to solve the Dynamic Economic Dispatch (DED) problem for a 9-bus power system with 3 generators over a 24-hour period. The objective is to determine the optimal generator outputs at each hour to minimize total generation costs while satisfying system constraints. PSO is applied to find the optimal solution by updating generator output positions based on personal and global best cost values. Results found the minimum cost schedule for each generator over the 24 hours while ensuring system limits were not violated.
Economic Load Dispatch (ELD) is a process of scheduling the required load demand among available generation units such that the fuel cost of operation is minimized. The ELD problem is formulated as a non-linear constrained optimization problem with both equality and inequality constraints. In this paper, two test systems of the ELD problems are solved by adopting the Cuckoo Search (CS) Algorithm. A comparison of obtained simulation results by using the CS is carried out against six other swarm intelligence algorithms: Particle Swarm Optimization, Shuffled Frog Leaping Algorithm, Bacterial Foraging Optimization, Artificial Bee Colony, Harmony Search and Firefly Algorithm. The effectiveness of each swarm intelligence algorithm is demonstrated on a test system comprising three-generators and other containing six-generators. Results denote superiority of the Cuckoo Search Algorithm and confirm its potential to solve the ELD problem.
Hybrid Optimization Approaches to Economic Load Dispatch Problems – A Compara...IRJET Journal
This document discusses various hybrid optimization techniques that have been proposed to solve economic load dispatch (ELD) problems. ELD problems aim to minimize the total fuel cost of generating units by considering constraints. The summary is:
1. Several hybrid optimization approaches combining techniques like particle swarm optimization, genetic algorithms, fuzzy logic, and artificial bee colony algorithms have been developed to solve ELD problems.
2. These hybrid methods are analyzed and shown to outperform traditional optimization techniques in terms of solution quality and computational time.
3. Case studies on standard test systems demonstrate that hybrid particle swarm optimization-direct search, chaotic particle swarm optimization-implicit filtering, and artificial bee colony-particle swarm optimization methods provide high quality solutions for the
This document presents a hybrid Gravitational Search Algorithm and Sequential Quadratic Programming (GSA-SQP) approach to solve economic emission load dispatch (EELD) problems in power systems. The approach aims to minimize both fuel costs and emission levels simultaneously while satisfying operational constraints. It formulates EELD as a multi-objective optimization problem involving non-linear, non-convex objectives and constraints. Numerical results on three test power systems show the proposed GSA-SQP hybrid approach provides better performing solutions compared to other evolutionary algorithms like NSGA-II and SPEA2.
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.
Locational marginal pricing framework in secured dispatch scheduling under co...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.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
Electronics system thermal management optimization using finite element and N...TELKOMNIKA JOURNAL
This document summarizes the optimization of electronics system thermal management using finite element analysis and the Nelder-Mead optimization method. A test sample with 3 components was modeled and optimized to minimize average temperature and area of the printed circuit board (PCB). The results showed temperature reductions of up to 4-8% and a 34% reduction in PCB area. Comparative analyses were also performed on samples from other studies, achieving temperature reductions of up to 23% and area reductions of up to 26%. Overall, the optimization approach significantly improved thermal management and performance while reducing PCB size.
Capacitor Placement and Reconfiguration of Distribution System with hybrid Fu...IOSR Journals
The document describes a hybrid fuzzy-opposition based differential evolution algorithm for capacitor placement and distribution system reconfiguration to minimize transmission losses and costs. The algorithm considers constraints like voltage limits and current limits while optimizing the objective function of total annual cost, which includes energy loss costs and capacitor costs. It was tested on the IEEE 33-bus distribution test system and able to reduce losses and satisfy power flow constraints.
Dynamic economic load dispatch a review of solution methodologies48jiten2k13
This document discusses various solution techniques for the economic load dispatch (ELD) problem in power systems. It first defines ELD and explains why it is important for minimizing generation costs while meeting load demands. The document then outlines different ELD formulation and solution methods like invasive weed optimization, particle swarm optimization, genetic algorithms, and simulated annealing. It provides flowcharts to illustrate the processes. The document also discusses the limitations of classical optimization methods for dynamic ELD problems and concludes with references used.
- The document discusses using a modified genetic algorithm to optimize parameters for automatic generation control of multi-area electric energy systems.
- It proposes a modified genetic algorithm that employs one-point crossover with modification. The crossover site helps maintain diversity of search points while exploiting known optimal values, balancing exploration and exploitation.
- The algorithm is used along with decomposition techniques and trapezoidal integration to determine optimal control parameters for multi-area systems and obtain better dynamic performance under small load perturbations, with and without considering nonlinearity from governor deadbands.
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 Dispatch using Quantum Evolutionary Algorithm in Electrical Power S...IJECEIAES
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Combining both Plug-in Vehicles and Renewable Energy Resources for Unit Commi...IOSR Journals
This document presents a study that combines plug-in electric vehicles with vehicle-to-grid technology (V2G), renewable energy resources like wind and solar, and existing power plants, to optimize unit commitment in smart grids. The goal is to minimize total costs and emissions. A genetic algorithm is used to optimize scheduling of generation units, V2G vehicles providing spinning reserves, and time-varying renewable sources over a 24-hour period to meet load demand at lowest cost while satisfying constraints. Simulation results validate that integrating V2G and renewable energy sources can effectively reduce costs and emissions for the smart grid.
Hybrid Particle Swarm Optimization for Solving Multi-Area Economic Dispatch P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) and RCGA.
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
This document presents an improved differential evolution algorithm for congestion management in power systems with wind turbine generators. The algorithm determines the optimal location of new wind farms based on bus sensitivity factor and wind availability factor. It then uses an enhanced differential evolution approach to reschedule generators and install new wind farms to relieve transmission line congestion. The algorithm is tested on the IEEE 30-bus system and is shown to be more effective at congestion management than other approaches.
PuShort Term Hydrothermal Scheduling using Evolutionary Programmingblished pa...Satyendra Singh
In this paper, Evolutionary Programming method
is used for short term hydrothermal scheduling which minimize
the total fuel cost while satisfying the constraints. This paper
developed and studies the performance of evolutionary programs
in solving hydrothermal scheduling problem. The effectiveness of
the developed program is tested for the system having one hydro
and one thermal unit for 24 hour load demand. Numerical results
show that highly near-optimal solutions can be obtained by
Evolutionary Programming.
The document summarizes a study on reducing CO2 emissions from thermal power plants through load dispatch scheduling. It presents equations to calculate CO2 emissions from power plants and describes using evolutionary algorithms to optimize load scheduling across three power plants. The results show evolutionary techniques achieved the lowest overall CO2 emissions of 8,426 tons compared to other methods, while maintaining the same total power output. The conclusion is that properly selecting which plants generate power through load scheduling can reduce CO2 emissions without additional equipment.
Comparisional Investigation of Load Dispatch Solutions with TLBO IJECEIAES
This paper discusses economic load dispatch Problem is modeled with nonconvex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This proposed algorithm is applied to solve the load dispatch problem for 6 unit and 10 unit test systems along with the other algorithms. This comparisional investigation explored various merits of TLBO with respect to PSO, DE, and HAS in the field economic load dispatch.
Multi-objective Optimization Scheme for PID-Controlled DC MotorIAES-IJPEDS
DC Motor is the most basic electro-mechanical equipment and well-known for its merit and simplicity. The performance of DC motor is assessed based on several qualities that are most-likely contradictory each other, i.e. settling time and overshoot percentage. Most of controller’s optimization problems are multi-objective in nature since they normally have several conflicting objectives that must be met simultaneously. In this study, the grey relational analysis (GRA) was combined with Taguchi method to search the optimum PID parameter for multi-objective problem. First, a L9 (33) orthogonal array was used to plan out the processing parameters that would affect the DC motor’s speed. Then GRA was applied to overcome the drawback of single quality characteristics in the Taguchi method, and then the optimized PID parameter combination was obtained for multiple quality characteristics from the response table and the response graph from GRA. Signal-to-noise ratio (S/N ratio) calculation and analysis of variance (ANOVA) would be performed to find out the significant factors. Lastly, the reliability and reproducibility of the experiment was verified by confirming a confidence interval (CI) of 95%.
Optimization of Economic Load Dispatch with Unit Commitment on Multi MachineIJAPEJOURNAL
Economic load dispatch (ELD) and Unit Commitment (UC) are significant research applications in power systems that optimize the total production cost of the predicted load demand. The UC problem determines a turn-on and turn-off schedule for a given combination of generating units, thus satisfying a set of dynamic operational constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the load demands of customers. The first phase in this project is to economically schedule the distribution of generating units using Gauss seidal and the second phase is to determine optimal load distribution for the scheduled units using dynamic programming method is applied to select and choose the combination of generating units that commit and de-commit during each hour. These precommitted schedules are optimized by dynamic programming method thus producing a global optimum solution with feasible and effective solution quality, minimal cost and time and higher precision. The effectiveness of the proposed techniques is investigated on two test systems consisting of five generating units and the experiments are carried out using MATLAB R2010b software. Experimental results prove that the proposed method is capable of yielding higher quality solution including mathematical simplicity, fast convergence, diversity maintenance, robustness and scalability for the complex ELD-UC problem.
Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization TechniquejournalBEEI
This document presents a study that uses Particle Swarm Optimization (PSO) technique to solve the Dynamic Economic Dispatch (DED) problem for a 9-bus power system with 3 generators over a 24-hour period. The objective is to determine the optimal generator outputs at each hour to minimize total generation costs while satisfying system constraints. PSO is applied to find the optimal solution by updating generator output positions based on personal and global best cost values. Results found the minimum cost schedule for each generator over the 24 hours while ensuring system limits were not violated.
Economic Load Dispatch (ELD) is a process of scheduling the required load demand among available generation units such that the fuel cost of operation is minimized. The ELD problem is formulated as a non-linear constrained optimization problem with both equality and inequality constraints. In this paper, two test systems of the ELD problems are solved by adopting the Cuckoo Search (CS) Algorithm. A comparison of obtained simulation results by using the CS is carried out against six other swarm intelligence algorithms: Particle Swarm Optimization, Shuffled Frog Leaping Algorithm, Bacterial Foraging Optimization, Artificial Bee Colony, Harmony Search and Firefly Algorithm. The effectiveness of each swarm intelligence algorithm is demonstrated on a test system comprising three-generators and other containing six-generators. Results denote superiority of the Cuckoo Search Algorithm and confirm its potential to solve the ELD problem.
Hybrid Optimization Approaches to Economic Load Dispatch Problems – A Compara...IRJET Journal
This document discusses various hybrid optimization techniques that have been proposed to solve economic load dispatch (ELD) problems. ELD problems aim to minimize the total fuel cost of generating units by considering constraints. The summary is:
1. Several hybrid optimization approaches combining techniques like particle swarm optimization, genetic algorithms, fuzzy logic, and artificial bee colony algorithms have been developed to solve ELD problems.
2. These hybrid methods are analyzed and shown to outperform traditional optimization techniques in terms of solution quality and computational time.
3. Case studies on standard test systems demonstrate that hybrid particle swarm optimization-direct search, chaotic particle swarm optimization-implicit filtering, and artificial bee colony-particle swarm optimization methods provide high quality solutions for the
This document presents a hybrid Gravitational Search Algorithm and Sequential Quadratic Programming (GSA-SQP) approach to solve economic emission load dispatch (EELD) problems in power systems. The approach aims to minimize both fuel costs and emission levels simultaneously while satisfying operational constraints. It formulates EELD as a multi-objective optimization problem involving non-linear, non-convex objectives and constraints. Numerical results on three test power systems show the proposed GSA-SQP hybrid approach provides better performing solutions compared to other evolutionary algorithms like NSGA-II and SPEA2.
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.
Locational marginal pricing framework in secured dispatch scheduling under co...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.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
Electronics system thermal management optimization using finite element and N...TELKOMNIKA JOURNAL
This document summarizes the optimization of electronics system thermal management using finite element analysis and the Nelder-Mead optimization method. A test sample with 3 components was modeled and optimized to minimize average temperature and area of the printed circuit board (PCB). The results showed temperature reductions of up to 4-8% and a 34% reduction in PCB area. Comparative analyses were also performed on samples from other studies, achieving temperature reductions of up to 23% and area reductions of up to 26%. Overall, the optimization approach significantly improved thermal management and performance while reducing PCB size.
Capacitor Placement and Reconfiguration of Distribution System with hybrid Fu...IOSR Journals
The document describes a hybrid fuzzy-opposition based differential evolution algorithm for capacitor placement and distribution system reconfiguration to minimize transmission losses and costs. The algorithm considers constraints like voltage limits and current limits while optimizing the objective function of total annual cost, which includes energy loss costs and capacitor costs. It was tested on the IEEE 33-bus distribution test system and able to reduce losses and satisfy power flow constraints.
Dynamic economic load dispatch a review of solution methodologies48jiten2k13
This document discusses various solution techniques for the economic load dispatch (ELD) problem in power systems. It first defines ELD and explains why it is important for minimizing generation costs while meeting load demands. The document then outlines different ELD formulation and solution methods like invasive weed optimization, particle swarm optimization, genetic algorithms, and simulated annealing. It provides flowcharts to illustrate the processes. The document also discusses the limitations of classical optimization methods for dynamic ELD problems and concludes with references used.
- The document discusses using a modified genetic algorithm to optimize parameters for automatic generation control of multi-area electric energy systems.
- It proposes a modified genetic algorithm that employs one-point crossover with modification. The crossover site helps maintain diversity of search points while exploiting known optimal values, balancing exploration and exploitation.
- The algorithm is used along with decomposition techniques and trapezoidal integration to determine optimal control parameters for multi-area systems and obtain better dynamic performance under small load perturbations, with and without considering nonlinearity from governor deadbands.
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 Dispatch using Quantum Evolutionary Algorithm in Electrical Power S...IJECEIAES
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Combining both Plug-in Vehicles and Renewable Energy Resources for Unit Commi...IOSR Journals
This document presents a study that combines plug-in electric vehicles with vehicle-to-grid technology (V2G), renewable energy resources like wind and solar, and existing power plants, to optimize unit commitment in smart grids. The goal is to minimize total costs and emissions. A genetic algorithm is used to optimize scheduling of generation units, V2G vehicles providing spinning reserves, and time-varying renewable sources over a 24-hour period to meet load demand at lowest cost while satisfying constraints. Simulation results validate that integrating V2G and renewable energy sources can effectively reduce costs and emissions for the smart grid.
Hybrid Particle Swarm Optimization for Solving Multi-Area Economic Dispatch P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) and RCGA.
Hybrid method for achieving Pareto front on economic emission dispatch IJECEIAES
In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multiobjective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II.
Economic Load Dispatch Optimization of Six Interconnected Generating Units Us...IOSR Journals
This document describes using particle swarm optimization (PSO) to solve the economic load dispatch (ELD) problem of optimizing the operation of six interconnected generating units. ELD aims to minimize total generation costs while satisfying constraints. PSO is applied to find optimal unit outputs that minimize cost, accounting for transmission losses. The proposed PSO approach is compared to genetic algorithms and conventional methods on a test system, showing PSO provides better solutions faster. Key steps of the PSO algorithm for ELD are initializing particles, evaluating fitness at each iteration, and updating personal and global best positions to iteratively improve solutions.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
Economic Dispatch of Generated Power Using Modified Lambda-Iteration MethodIOSR Journals
This document proposes a modified lambda-iteration method for solving economic dispatch problems and minimizing fuel costs. It involves determining the optimal power output of each generator given constraints like load demand and transmission losses. The method is implemented in MATLAB and tested on a 6 generator system. Results found the total power was 1263.0074MW at an incremental cost of 13.2539$/MWh, close to those from a genetic algorithm solution. The proposed method provides a fast, easy to use approach for economic dispatch optimization problems.
The document describes the economic environmental dispatch (EED) problem, which aims to minimize both the fuel cost and emissions of fossil fuel power plants simultaneously while satisfying operational constraints. The EED problem is formulated as a multi-objective optimization problem with conflicting cost and emission objectives and equality and inequality constraints. Multi-objective differential evolution is proposed to solve the EED problem and find the Pareto optimal solutions. Test results show the proposed approach performs comparably or better than other multi-objective evolutionary algorithms for the EED problem.
This document presents a traditional approach called the lambda iteration method to solve the economic load dispatch (ELD) problem considering generator constraints. The ELD problem aims to minimize the total fuel cost while meeting demand and generator constraints. The lambda iteration method is implemented on a three-unit and six-unit system, with and without transmission losses, in MATLAB. The results show that considering transmission losses provides a more accurate solution to the ELD problem compared to ignoring losses. The lambda iteration method provides an effective traditional technique for solving the ELD problem.
ECONOMIC LOAD DISPATCH USING GENETIC ALGORITHMIJARIIT
This paper present the application of Genetic Algorithm (GA) to Economic Load Dispatch problem of the power system. Economic Load Dispatch is one of the major optimization problems dealing with the modern power systems.ELD determines the electrical power to be generated by the committed generating units in a power system so that the total generation cost of the system is minimized, while satisfactory the load demand. The objective is to minimize the total generation fuel cost and maintain the power flow within safety limits. The introduced algorithm has been demonstrated for the given test systems considering the transmission line losses.
Optimal Operation of Wind-thermal generation using differential evolutionIOSR Journals
This document presents an optimal operation model for a wind-thermal power generation system using differential evolution (DE). DE is an evolutionary algorithm inspired by biological evolution that can solve complex constrained optimization problems. The paper formulates the economic dispatch problem to minimize total generation cost of the wind and thermal plants subject to various constraints like power balance, generator limits, ramp rates, and valve point loading effects. Five different DE mutation strategies are analyzed for solving the wind-thermal economic dispatch problem on a test system with 10 thermal units. The results show that the best mutation strategy and control parameter values (mutation rate and crossover rate) depend on the problem and can significantly impact the solution quality and consistency obtained by the DE algorithm.
Evolutionary algorithm solution for economic dispatch problemsIJECEIAES
A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints, these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed, the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.
Comparative study of the price penalty factors approaches for Bi-objective di...IJECEIAES
One of the main objectives of electricity dispatch centers is to schedule the operation of available generating units to meet the required load demand at minimum operating cost with minimum emission level caused by fossil-based power plants. Finding the right balance between the fuel cost the green gasemissionsis reffered as Combined Economic and Emission Dispatch (CEED) problem which is one of the important optimization problems related the operationmodern power systems. The Particle Swarm Optimization algorithm (PSO) is a stochastic optimization technique which is inspired from the social learning of birds or fishes. It is exploited to solve CEED problem. This paper examines the impact of six penalty factors like "Min-Max", "Max-Max", "Min-Min", "Max-Min", "Average" and "Common" price penalty factors for solving CEED problem. The Price Penalty Factor for the CEED is the ratio of fuel cost to emission value. This bi-objective dispatch problem is investigated in the Real West Algeria power network consisting of 22 buses with 7 generators. Results prove capability of PSO in solving CEED problem with various penalty factors and it proves that Min-Max price penalty factor provides the best compromise solution in comparison to the other penalty factors.
Multi-objective based economic environmental dispatch with stochastic solar-w...IJECEIAES
This paper presents an evolutionary based technique for solving the multi-objective based economic environmental dispatch by considering the stochastic behavior of renewable energy resources (RERs). The power system considered in this paper consists of wind and solar photovoltaic (PV) generators along with conventional thermal energy generators. The RERs are environmentally friendlier, but their intermittent nature affects the system operation. Therefore, the system operator should be aware of these operating conditions and schedule the power output from these resources accordingly. In this paper, the proposed EED problem is solved by considering the nonlinear characteristics of thermal generators, such as ramp rate, valve point loading (VPL), and prohibited operating zones (POZs) effects. The stochastic nature of RERs is handled by the probability distribution analysis. The aim of proposed optimization problem is to minimize operating cost and emission levels by satisfying various operational constraints. In this paper, the single objective optimization problems are solved by using particle swarm optimization (PSO) algorithm, and the multi-objective optimization problem is solved by using the multi-objective PSO algorithm. The feasibility of proposed approach is demonstrated on six generator power system.
Optimal Unit Commitment Based on Economic Dispatch Using Improved Particle Sw...paperpublications3
The document presents an improved particle swarm optimization (IPSO) algorithm for solving the optimal unit commitment problem in power systems. The IPSO algorithm extends the standard PSO algorithm by using additional particle information to control mutation and mimic social behaviors. The algorithm was implemented on the IEEE 14 bus test system in MATLAB. Results showed the IPSO approach committed units to meet load demand over 24 hours while satisfying constraints, with bus voltages maintained between 1.0017 and 1.0751 per unit. Total costs including fuel, startup, and shutdown costs were minimized at each hour.
The document describes a two-stage method for optimal allocation of capacitors in a radial distribution system. In the first stage, loss sensitivity factors are used to calculate candidate locations for capacitors. In the second stage, a harmony search algorithm is used to minimize total costs, including capacitor costs and power loss costs, by determining the optimal capacitor sizes and numbers placed at the candidate locations. The method is tested on 33-bus and 69-bus test systems and results in reduced power losses and costs compared to the base case without capacitors.
This paper discusses the possible applications of particle swarm optimization (PSO) in the Power system. One of the problems in Power System is Economic Load dispatch (ED). The discussion is carried out in view of the saving money, computational speed – up and expandability that can be achieved by using PSO method. The general approach of the method of this paper is that of Dynamic Programming Method coupled with PSO method. The feasibility of the proposed method is demonstrated, and it is compared with the lambda iterative method in terms of the solution quality and computation efficiency. The experimental results show that the proposed PSO method was indeed capable of obtaining higher quality solutions efficiently in ED problems.
Inclusion of environmental constraints into siting and sizingIAEME Publication
This document summarizes a research paper that investigates including environmental constraints, specifically carbon dioxide (CO2) emissions, in the siting and sizing techniques used to determine optimal locations and capacities for localized gas turbine distributed generation units. The paper introduces a methodology to model CO2 emissions from both distributed generation units and centralized power stations based on their emission factors, power output, and other variables. The emissions constraint is incorporated into an existing distributed generation siting and sizing optimization model. The model is then applied to a case study of a real power distribution network to determine the optimal distributed generation configurations while accounting for environmental impacts.
IRJET- Solving Economic Load Dispatch Problem with Valve Point EffectIRJET Journal
This document presents a study on using Jaya Optimization (JO) to solve the economic load dispatch (ELD) problem considering valve point loading effects. ELD aims to minimize fuel costs while meeting demand, and involves constraints. JO is applied to a 13-unit system, minimizing costs while satisfying constraints. Results show JO finds the optimal solution of $17937.67/hr, outperforming other algorithms like SDE, IGA_MU, and HQPSO. JO is thus an effective technique for solving the non-linear, non-convex ELD problem with valve point effects.
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
The study explores the reasons for a transgender to become entrepreneurs. In this study transgender entrepreneur was taken as independent variable and reasons to become as dependent variable. Data were collected through a structured questionnaire containing a five point Likert Scale. The study examined the data of 30 transgender entrepreneurs in Salem Municipal Corporation of Tamil Nadu State, India. Simple Random sampling technique was used. Garrett Ranking Technique (Percentile Position, Mean Scores) was used as the analysis for the present study to identify the top 13 stimulus factors for establishment of trans entrepreneurial venture. Economic advancement of a nation is governed upon the upshot of a resolute entrepreneurial doings. The conception of entrepreneurship has stretched and materialized to the socially deflated uncharted sections of transgender community. Presently transgenders have smashed their stereotypes and are making recent headlines of achievements in various fields of our Indian society. The trans-community is gradually being observed in a new light and has been trying to achieve prospective growth in entrepreneurship. The findings of the research revealed that the optimistic changes are taking place to change affirmative societal outlook of the transgender for entrepreneurial ventureship. It also laid emphasis on other transgenders to renovate their traditional living. The paper also highlights that legislators, supervisory body should endorse an impartial canons and reforms in Tamil Nadu Transgender Welfare Board Association.
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
Since ages gender difference is always a debatable theme whether caused by nature, evolution or environment. The birth of a transgender is dreadful not only for the child but also for their parents. The pain of living in the wrong physique and treated as second class victimized citizen is outrageous and fully harboured with vicious baseless negative scruples. For so long, social exclusion had perpetuated inequality and deprivation experiencing ingrained malign stigma and besieged victims of crime or violence across their life spans. They are pushed into the murky way of life with a source of eternal disgust, bereft sexual potency and perennial fear. Although they are highly visible but very little is known about them. The common public needs to comprehend the ravaged arrogance on these insensitive souls and assist in integrating them into the mainstream by offering equal opportunity, treat with humanity and respect their dignity. Entrepreneurship in the current age is endorsing the gender fairness movement. Unstable careers and economic inadequacy had inclined one of the gender variant people called Transgender to become entrepreneurs. These tiny budding entrepreneurs resulted in economic transition by means of employment, free from the clutches of stereotype jobs, raised standard of living and handful of financial empowerment. Besides all these inhibitions, they were able to witness a platform for skill set development that ignited them to enter into entrepreneurial domain. This paper epitomizes skill sets involved in trans-entrepreneurs of Thoothukudi Municipal Corporation of Tamil Nadu State and is a groundbreaking determination to sightsee various skills incorporated and the impact on entrepreneurship.
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
The banking and financial services industries are experiencing increased technology penetration. Among them, the banking industry has made technological advancements to better serve the general populace. The economy focused on transforming the banking sector's system into a cashless, paperless, and faceless one. The researcher wants to evaluate the user's intention for utilising a mobile banking application. The study also examines the variables affecting the user's behaviour intention when selecting specific applications for financial transactions. The researcher employed a well-structured questionnaire and a descriptive study methodology to gather the respondents' primary data utilising the snowball sampling technique. The study includes variables like performance expectations, effort expectations, social impact, enabling circumstances, and perceived risk. Each of the aforementioned variables has a major impact on how users utilise mobile banking applications. The outcome will assist the service provider in comprehending the user's history with mobile banking applications.
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
Technology upgradation in banking sector took the economy to view that payment mode towards online transactions using mobile applications. This system enabled connectivity between banks, Merchant and user in a convenient mode. there are various applications used for online transactions such as Google pay, Paytm, freecharge, mobikiwi, oxygen, phonepe and so on and it also includes mobile banking applications. The study aimed at evaluating the predilection of the user in adopting digital transaction. The study is descriptive in nature. The researcher used random sample techniques to collect the data. The findings reveal that mobile applications differ with the quality of service rendered by Gpay and Phonepe. The researcher suggest the Phonepe application should focus on implementing the application should be user friendly interface and Gpay on motivating the users to feel the importance of request for money and modes of payments in the application.
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
The prototype of a voice-based ATM for visually impaired using Arduino is to help people who are blind. This uses RFID cards which contain users fingerprint encrypted on it and interacts with the users through voice commands. ATM operates when sensor detects the presence of one person in the cabin. After scanning the RFID card, it will ask to select the mode like –normal or blind. User can select the respective mode through voice input, if blind mode is selected the balance check or cash withdraw can be done through voice input. Normal mode procedure is same as the existing ATM.
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends for conflict management as an integral part of effective human resource management.
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
Our life journey, in general, is closely defined by the way we understand the meaning of why we coexist and deal with its challenges. As we develop the "inspiration economy", we could say that nearly all of the challenges we have faced are opportunities that help us to discover the rest of our journey. In this note paper, we explore how being faced with the opportunity of being a close carer for an aging parent with dementia brought intangible discoveries that changed our insight of the meaning of the rest of our life journey.
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
The main objective of this study is to analyze the impact of aspects of Organizational Culture on the Effectiveness of the Performance Management System (PMS) in the Health Care Organization at Thanjavur. Organizational Culture and PMS play a crucial role in present-day organizations in achieving their objectives. PMS needs employees’ cooperation to achieve its intended objectives. Employees' cooperation depends upon the organization’s culture. The present study uses exploratory research to examine the relationship between the Organization's culture and the Effectiveness of the Performance Management System. The study uses a Structured Questionnaire to collect the primary data. For this study, Thirty-six non-clinical employees were selected from twelve randomly selected Health Care organizations at Thanjavur. Thirty-two fully completed questionnaires were received.
Living in 21st century in itself reminds all of us the necessity of police and its administration. As more and more we are entering into the modern society and culture, the more we require the services of the so called ‘Khaki Worthy’ men i.e., the police personnel. Whether we talk of Indian police or the other nation’s police, they all have the same recognition as they have in India. But as already mentioned, their services and requirements are different after the like 26th November, 2008 incidents, where they without saving their own lives has sacrificed themselves without any hitch and without caring about their respective family members and wards. In other words, they are like our heroes and mentors who can guide us from the darkness of fear, militancy, corruption and other dark sides of life and so on. Now the question arises, if Gandhi would have been alive today, what would have been his reaction/opinion to the police and its functioning? Would he have some thing different in his mind now what he had been in his mind before the partition or would he be going to start some Satyagraha in the form of some improvement in the functioning of the police administration? Really these questions or rather night mares can come to any one’s mind, when there is too much confusion is prevailing in our minds, when there is too much corruption in the society and when the polices working is also in the questioning because of one or the other case throughout the India. It is matter of great concern that we have to thing over our administration and our practical approach because the police personals are also like us, they are part and parcel of our society and among one of us, so why we all are pin pointing towards them.
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
The goal of this study was to see how talent management affected employee retention in the selected IT organizations in Chennai. The fundamental issue was the difficulty to attract, hire, and retain talented personnel who perform well and the gap between supply and demand of talent acquisition and retaining them within the firms. The study's main goals were to determine the impact of talent management on employee retention in IT companies in Chennai, investigate talent management strategies that IT companies could use to improve talent acquisition, performance management, career planning and formulate retention strategies that the IT firms could use. The respondents were given a structured close-ended questionnaire with the 5 Point Likert Scale as part of the study's quantitative research design. The target population consisted of 289 IT professionals. The questionnaires were distributed and collected by the researcher directly. The Statistical Package for Social Sciences (SPSS) was used to collect and analyse the questionnaire responses. Hypotheses that were formulated for the various areas of the study were tested using a variety of statistical tests. The key findings of the study suggested that talent management had an impact on employee retention. The studies also found that there is a clear link between the implementation of talent management and retention measures. Management should provide enough training and development for employees, clarify job responsibilities, provide adequate remuneration packages, and recognise employees for exceptional performance.
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
Globally, Millions of dollars were spent by the organizations for employing skilled Information Technology (IT) professionals. It is costly to replace unskilled employees with IT professionals possessing technical skills and competencies that aid in interconnecting the business processes. The organization’s employment tactics were forced to alter by globalization along with technological innovations as they consistently diminish to remain lean, outsource to concentrate on core competencies along with restructuring/reallocate personnel to gather efficiency. As other jobs, organizations or professions have become reasonably more appropriate in a shifting employment landscape, the above alterations trigger both involuntary as well as voluntary turnover. The employee view on jobs is also afflicted by the COVID-19 pandemic along with the employee-driven labour market. So, having effective strategies is necessary to tackle the withdrawal rate of employees. By associating Emotional Intelligence (EI) along with Talent Management (TM) in the IT industry, the rise in attrition rate was analyzed in this study. Only 303 respondents were collected out of 350 participants to whom questionnaires were distributed. From the employees of IT organizations located in Bangalore (India), the data were congregated. A simple random sampling methodology was employed to congregate data as of the respondents. Generating the hypothesis along with testing is eventuated. The effect of EI and TM along with regression analysis between TM and EI was analyzed. The outcomes indicated that employee and Organizational Performance (OP) were elevated by effective EI along with TM.
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
By implementing talent management strategy, organizations would have the option to retain their skilled professionals while additionally working on their overall performance. It is the course of appropriately utilizing the ideal individuals, setting them up for future top positions, exploring and dealing with their performance, and holding them back from leaving the organization. It is employee performance that determines the success of every organization. The firm quickly obtains an upper hand over its rivals in the event that its employees having particular skills that cannot be duplicated by the competitors. Thus, firms are centred on creating successful talent management practices and processes to deal with the unique human resources. Firms are additionally endeavouring to keep their top/key staff since on the off chance that they leave; the whole store of information leaves the firm's hands. The study's objective was to determine the impact of talent management on organizational performance among the selected IT organizations in Chennai. The study recommends that talent management limitedly affects performance. On the off chance that this talent is appropriately management and implemented properly, organizations might benefit as much as possible from their maintained assets to support development and productivity, both monetarily and non-monetarily.
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
Banking regulations act of India, 1949 defines banking as “acceptance of deposits for the purpose of lending or investment from the public, repayment on demand or otherwise and withdrawable through cheques, drafts order or otherwise”, the major participants of the Indian financial system are commercial banks, the financial institution encompassing term lending institutions. Investments institutions, specialized financial institution and the state level development banks, non banking financial companies (NBFC) and other market intermediaries such has the stock brokers and money lenders are among the oldest of the certain variants of NBFC and the oldest market participants. The asset quality of banks is one of the most important indicators of their financial health. The Indian banking sector has been facing severe problems of increasing Non- Performing Assets (NPAs). The NPAs growth directly and indirectly affects the quality of assets and profitability of banks. It also shows the efficiency of banks credit risk management and the recovery effectiveness. NPA do not generate any income, whereas, the bank is required to make provisions for such as assets that why is a double edge weapon. This paper outlines the concept of quality of bank loans of different types like Housing, Agriculture and MSME loans in state Haryana of selected public and private sector banks. This study is highlighting problems associated with the role of commercial bank in financing Small and Medium Scale Enterprises (SME). The overall objective of the research was to assess the effect of the financing provisions existing for the setting up and operations of MSMEs in the country and to generate recommendations for more robust financing mechanisms for successful operation of the MSMEs, in turn understanding the impact of MSME loans on financial institutions due to NPA. There are many research conducted on the topic of Non- Performing Assets (NPA) Management, concerning particular bank, comparative study of public and private banks etc. In this paper the researcher is considering the aggregate data of selected public sector and private sector banks and attempts to compare the NPA of Housing, Agriculture and MSME loans in state Haryana of public and private sector banks. The tools used in the study are average and Anova test and variance. The findings reveal that NPA is common problem for both public and private sector banks and is associated with all types of loans either that is housing loans, agriculture loans and loans to SMES. NPAs of both public and private sector banks show the increasing trend. In 2010-11 GNPA of public and private sector were at same level it was 2% but after 2010-11 it increased in many fold and at present there is GNPA in some more than 15%. It shows the dark area of Indian banking sector.
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
An experiment conducted in this study found that BaSO4 changed Nylon 6's mechanical properties. By changing the weight ratios, BaSO4 was used to make Nylon 6. This Researcher looked into how hard Nylon-6/BaSO4 composites are and how well they wear. Experiments were done based on Taguchi design L9. Nylon-6/BaSO4 composites can be tested for their hardness number using a Rockwell hardness testing apparatus. On Nylon/BaSO4, the wear behavior was measured by a wear monitor, pinon-disc friction by varying reinforcement, sliding speed, and sliding distance, and the microstructure of the crack surfaces was observed by SEM. This study provides significant contributions to ultimate strength by increasing BaSO4 content up to 16% in the composites, and sliding speed contributes 72.45% to the wear rate
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
The majority of the population in India lives in villages. The village is the back bone of the country. Village or rural industries play an important role in the national economy, particularly in the rural development. Developing the rural economy is one of the key indicators towards a country’s success. Whether it be the need to look after the welfare of the farmers or invest in rural infrastructure, Governments have to ensure that rural development isn’t compromised. The economic development of our country largely depends on the progress of rural areas and the standard of living of rural masses. Village or rural industries play an important role in the national economy, particularly in the rural development. Rural entrepreneurship is based on stimulating local entrepreneurial talent and the subsequent growth of indigenous enterprises. It recognizes opportunity in the rural areas and accelerates a unique blend of resources either inside or outside of agriculture. Rural entrepreneurship brings an economic value to the rural sector by creating new methods of production, new markets, new products and generate employment opportunities thereby ensuring continuous rural development. Social Entrepreneurship has the direct and primary objective of serving the society along with the earning profits. So, social entrepreneurship is different from the economic entrepreneurship as its basic objective is not to earn profits but for providing innovative solutions to meet the society needs which are not taken care by majority of the entrepreneurs as they are in the business for profit making as a sole objective. So, the Social Entrepreneurs have the huge growth potential particularly in the developing countries like India where we have huge societal disparities in terms of the financial positions of the population. Still 22 percent of the Indian population is below the poverty line and also there is disparity among the rural & urban population in terms of families living under BPL. 25.7 percent of the rural population & 13.7 percent of the urban population is under BPL which clearly shows the disparity of the poor people in the rural and urban areas. The need to develop social entrepreneurship in agriculture is dictated by a large number of social problems. Such problems include low living standards, unemployment, and social tension. The reasons that led to the emergence of the practice of social entrepreneurship are the above factors. The research problem lays upon disclosing the importance of role of social entrepreneurship in rural development of India. The paper the tendencies of social entrepreneurship in India, to present successful examples of such business for providing recommendations how to improve situation in rural areas in terms of social entrepreneurship development. Indian government has made some steps towards development of social enterprises, social entrepreneurship, and social in- novation, but a lot remains to be improved.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
Manufacturing industries have witnessed an outburst in productivity. For productivity improvement manufacturing industries are taking various initiatives by using lean tools and techniques. However, in different manufacturing industries, frugal approach is applied in product design and services as a tool for improvement. Frugal approach contributed to prove less is more and seems indirectly contributing to improve productivity. Hence, there is need to understand status of frugal approach application in manufacturing industries. All manufacturing industries are trying hard and putting continuous efforts for competitive existence. For productivity improvements, manufacturing industries are coming up with different effective and efficient solutions in manufacturing processes and operations. To overcome current challenges, manufacturing industries have started using frugal approach in product design and services. For this study, methodology adopted with both primary and secondary sources of data. For primary source interview and observation technique is used and for secondary source review has done based on available literatures in website, printed magazines, manual etc. An attempt has made for understanding application of frugal approach with the study of manufacturing industry project. Manufacturing industry selected for this project study is Mahindra and Mahindra Ltd. This paper will help researcher to find the connections between the two concepts productivity improvement and frugal approach. This paper will help to understand significance of frugal approach for productivity improvement in manufacturing industry. This will also help to understand current scenario of frugal approach in manufacturing industry. In manufacturing industries various process are involved to deliver the final product. In the process of converting input in to output through manufacturing process productivity plays very critical role. Hence this study will help to evolve status of frugal approach in productivity improvement programme. The notion of frugal can be viewed as an approach towards productivity improvement in manufacturing industries.
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
In this paper, we investigated a queuing model of fuzzy environment-based a multiple channel queuing model (M/M/C) ( /FCFS) and study its performance under realistic conditions. It applies a nonagonal fuzzy number to analyse the relevant performance of a multiple channel queuing model (M/M/C) ( /FCFS). Based on the sub interval average ranking method for nonagonal fuzzy number, we convert fuzzy number to crisp one. Numerical results reveal that the efficiency of this method. Intuitively, the fuzzy environment adapts well to a multiple channel queuing models (M/M/C) ( /FCFS) are very well.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.