Search Results - ((solutions OR (evolutionary OR evolutionary)) OR (evolution OR solution)) 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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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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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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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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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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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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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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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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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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A power flow solvability identification and calculation algorithm using evolutionary programming (EP) / Kahardi Muhammad Talib by Muhammad Talib, Kahardi

Subjects: “…Evolutionary programming (Computer science). Genetic algorithms…”
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A Systematic Exploration of Mutation Space in a Hybridized Interactive Evolutionary Programming for Mobile Game Programming by Jia Hui Ong, Jason Teo

“…Evolutionary programming is the core Evolutionary Algorithm (EA) used in this study where it is hybridized with Interactive Evolutionary Algorithm (IEA) to generate different rulesets that was played on a custom arcade-type mobile game. …”
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Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim by Md Daim, Mohd Khairil Izwan

“…This project presents a new technique for solving the optimal power flow problem, in a power system using an Evolutionary Programming and Immune Evolution Programming optimization technique. …”
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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. …”

Evolutionary Programming (EP) for optimal Static Var Compensator sizing in distribution system / Hanem Saad by Saad, Hanem

“…This report presents a Evolutionary Programming for optimization and automatic control of reactive power in distribution feeders and substations. …”
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Solving unit commitment problem with wind power energy using multi agent evolutionary programming optimization technique: article / Mohd Ikhwan Mahasan by Mahasan, Mohd Ikhwan

“…Multi Agent Evolutionary Programming is a combination of two Artificial Intelligent techniques which are Multi Agent System and Evolutionary Programming.…”
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Comparison of Artificial Immune System (AIS) and Multiagent Immune Evolutionary Programming (MAIEP) in solving economic dispatch problem: article / Noor Aziela Mat Zin by Mat Zin, Noor Aziela

“…Artificial Immune System has the characteristic such as ability of learning, memory, recognition, self-organizing and adaptive, while Multiagent Immune Evolutionary Programming is a combination of Multiagent System, Evolutionary Programming and Artificial Immune System. …”
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