Search Results - ((((solution OR solution) OR solution) OR evolutionary) OR evolution) programming

Minimization of power loss by evolutionary programming using Thyristor Controlled Series Compensators (TCSC) / Fazleza Abdul Latiff by Abdul Latiff, Fazleza

“…This approach is done by using Evolutionary Programming (EP) technique. EP search for the optimal solution by evolving a population of candidate solutions, over a number of generations or iterations. …”
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Solving load flow solution using evolutionary programming method / Nurul-Huda Ismail by Ismail, Nurul-Huda

Subjects: “…Evolutionary programming (Computer science). Genetic algorithms…”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Solving unit commitment problem with wind energy using artificial immune evolutionary programming optimization technique / Mohamad Fitri Ramli by Ramli, Mohamad Fitri

“…This project proposes a solution to unit commitment problem with wind power using artificial immune evolutionary programming. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

Subjects: “…Evolutionary programming (Computer science). Genetic algorithms…”
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Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Solving unit commitment with wind power using artificial immune evolutionary programming optimization technique: article / Mohamad Fitri Ramli by Ramli, Mohamad Fitri

“…This paper propose a solution to unit commitment problem with wind power using artificial immune evolutionary programming The objective of this paper is to find the suitable generation scheduling which can minimize the operation cost with subjmted to various constrain The main idea of this paper is to integrate the use of Artificial fmmune Evolutionary Programming as optimization technique towards Unit Commitment Other than that, this paper also aiming to ieview the effect of addition wind power to the Unit Commitment problem solution. …”
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Customer profiling-based optimal load shaving solution using Evolutionary Programming technique: article by Zainudin, Muhd Ezzad Zaqwan

“…This paper presents optimal load clipping and shifting using Evolutionary Programming (EP) technique. The problem formulation is based on the basic load clipping and load shifting knowledge. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

“…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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Power System Controlled Islanding using Modified Discrete Optimization Techniques by Saharuddin N.Z., Abidin I.Z., Mokhlis H., Hassan M.Y.

“…Computer programming; Distributed power generation; Electric lines; Electric power system control; Electric power transmission; Light transmission; Particle swarm optimization (PSO); Power control; Controlled islanding; Discrete particle swarm optimization; Evolutionary programming techniques; Minimal power; Minimal power flow disruption; Modified discrete evolutionary programming technique; Modified discrete particle swarm optimization technique; Particle swarm optimization technique; Power flows; Power imbalance; Electric load flow…”

An improved grey wolf with whale algorithm for optimization functions by Asgher, Hafiz Maaz

“…Since its inception in 2014, GWO is able to successfully solve several optimization problems and has shown better convergence than the Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Differential Evolution (DE), and Evolutionary Programming (EP). …”
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Discrete Evolutionary Programming for Network Splitting Strategy: Different Mutation Technique by Saharuddin, Nur Zawani, Abidin, Izham Zainal, Mokhlis, Hazlie

“…Therefore, this paper investigates two different mutation techniques; single-level and three-level mutation, utilized in Discrete Evolutionary Programming (DEP) optimization to find the optimal splitting solution following a critical line outage. …”
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Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List by Othman M.N.C., Rahman T.K.A., Mokhlis H., Aman M.M.

“…The search process is refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. The developed technique is tested on ten generating units test system for a 24-h scheduling period, and the results are compared with the standard Evolutionary Programming (EP), Evolutionary Programming with Priority Listing (EP-PL) and Multi-agent Evolutionary Programming (MAEP) optimisation techniques. …”

Customer profiling-based optimal load shaving solution using evolutionary programming technique / Muhammad Ezzad Zaqwan Zainudin by Zainudin, Muhammad Ezzad Zaqwan

“…This thesis presents optimal load clipping and shifting using Evolutionary Programming (EP) technique. The problem formulation is based on the basic load clipping and load shifting knowledge. …”
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