Search Results - (( using (evolutionary OR solution) based algorithm ) OR ( using optimization _ algorithm ))
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Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems
Published 2015“…The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. …”
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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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Multi-objective optimization of all-wheel drive electric formula vehicle for performance and energy efficiency using evolutionary algorithms
Published 2020“…A new method based on constraint multi-objective optimization using evolutionary algorithms is proposed to optimize the powertrain design of a battery electric formula vehicle with an all-wheel independent motor drive. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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Exploring fruit fly evolutionary algorithm in a university examination timetabling environment
Published 2019“…A new evolutionary algorithm namely the Fruit-Fly Optimization Algorithm (FOA) which is based on the behavior of finding food by the fruit fly is used as solution methodology. …”
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Maintain optimal configurations for large configurable systems using multi-objective optimization
Published 2022“…The proposed approach is also used to generate the optimized test suites with the help of different multi-objective Evolutionary Algorithms (MOEAs).…”
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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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Evolutionary mating algorithm
Published 2023“…This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. …”
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Design of digital circuit structure based on evolutionary algorithm method
Published 2008“…Evolutionary Algorithms (EAs) cover all the applications involving the use of Evolutionary Computation in electronic system design. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…Thus, selective crossover rate and mutation rate from a literature was referred and used in the later experiments. The second experiment result shows both GA and DE algorithms can generate optimal solutions with very high fitness scores but the cost of spawning was extremely high. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Towards Software Product Lines Optimization Using Evolutionary Algorithms
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Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman
Published 2021“…Initially, Iterative-based Sizing Algorithm (ISA) which uses the non-computational intelligence-based approach is presented to serve as the benchmark for computational intelligence (CI)-based sizing algorithm. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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Optimization of energy management and conversion in the water systems based on evolutionary algorithms
Published 2019“…In addition, genetic algorithm (GA) and particle swarm optimization algorithm (PSOA) have been used as successful algorithms in such engineering application for optimizations in order to introduce a comprehensive comparison analysis with the results of WOA. …”
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Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis
Published 2019“…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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