Search Results - evaluation _ differences evolutionary algorithm
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Evaluation of fast evolutionary programming, firefly algorithm and mutate-cuckoo search algorithm in single-objective optimization / Muhammad Zakyizzuddin Rosselan, Shahril Irwan S...
Published 2016“…In this study proposes an evaluation of different computational intelligences, i.e Fast-Evolutionary Algorithm (FEP), Firefly Algorithm (FA) and Mutate-cuckoo Search Algorithm (MCSA) for solving single-objective optimization problem. …”
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A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints
Published 2016“…Practically allevolutionary optimization studies have focused exclusively on the use of number of fitness evaluations as the constraining factor when comparing different evolutionary algorithms (EAs). …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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Global optimal analysis of variant genetic operations in solar tracking
Published 2023“…Lots of research has been carried out in solar tracking system using different types of Evolutionary Algorithm. In this research, genetic algorithm is explored to maximize the performance of solar tracking system. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…To evaluate the hybrid algorithm, optimization of hydro-power energy of Karun dams were considered. …”
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Enhancing solid oxide fuel cell efficiency through advanced model identification using differential evolutionary mutation fennec fox algorithm
Published 2025“…This research introduces a novel approach for optimal SOFC model identification using a differential evolutionary mutation Fennec fox algorithm (DEMFFA). …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…Evolutionary algorithms have been extensively used to resolve problems associated with multiple and often conflicting objectives. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…As a comparative study, the performance of the algorithms was evaluated based on various standard metrics. …”
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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). It has demonstrated good convergence, and its principles are easy to understand. …”
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Performance evaluation of chaos-enhanced stochastic fractal search algorithm using constrained engineering design problems
Published 2017“…This paper presents the performance evaluation of Chaos-enhanced Stochastic Fractal Search (CFS) algorithms for solving three different constrained engineering design optimization problems which extensively were used in the literature as a benchmarking task. …”
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Identifying movement of object in multiple images via particle swarm optimization algorithm / Mohd Haidhar Iqbal Hassan
Published 2016“…This project used one of algorithm from category Evolutionary Computing (EC) and that algorithm is Particle Swarm Optimization (PSO). …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…The main motivation for this study is to introduce and evaluate an advance new customized GA. Comparison results of different combinatorial operators and tests with different probability factors are shown. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…The main motivation for this study is to introduce and evaluate an advance new customized GA. Comparison results of different combinatorial operators and tests with different probability factors are shown. …”
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