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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…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
Published 2023“…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
Published 2023“…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
Published 2023“…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
Published 2023“…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
Published 2023“…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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Evolutionary and population dynamics of 3 parents differential evolution (3PDE) using self-adaptive tuning methodologies
Published 2011“…In this paper, 50 repeated evolutionary runs for each of 20 well-known benchmarks were carried out to test the proposed algorithms against the original 4-parents DE algorithm. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Due to the effective attraction-repulsion mechanism of electromagnetic-like (EM) algorithm and reliable exploration and exploitation phases of differential evolution (DE), these two methods were used to determine parameters of the single diode PV model and finding optimal sizing of the SAPV system. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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An Approach to Derive Parametric L-System Using Genetic Algorithm
Published 2009“…This paper examines a method for automatic plant modeling which is based on an integration of GA and Parametric L-System using appropriate fitness function. …”
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Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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New scaling of bracketing method for fourth and sixth section / Nur Aizat Noor Manshah & Nurhidayatul Liyana Mohd Mustafa
Published 2019Subjects: “…Analytical methods used in the solution of physical problems…”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…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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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…In this paper, the filter method chi square and the Artificial Bee Colony) ABC algorithm were both used as FS methods . …”
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Economic power dispatch solution with non-smooth cost functions using differential evolution: article / Muhammad Firdaus Abd Rahim
Published 2011“…This thesis proposes a solution for Economic Dispatch problems with non-smooth cost functions using Differential Evolution (DE) algorithm. …”
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Optimisation of neural network with simultaneous feature selection and network prunning using evolutionary algorithm
Published 2015“…Most advances on the Evolutionary Algorithm optimisation of Neural Network are on recurrent neural network using the NEAT optimisation method. …”
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