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1
Crossover-first differential evolution for improved global optimization in non-uniform search landscapes
Published 2015“…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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2
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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Global optimal analysis of variant genetic operations in solar tracking
Published 2023“…Genetic Algorithms (GAs), Evolution Strategies (ES), Evolutionary Programming (EP) and Genetic Programming (GP) are some of the best known types of Evolutionary Algorithm (EA)where it is a class of global search algorithms inspired by natural evolution. …”
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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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5
Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…An improved version of Differential Evolution (DE) namely Backtracking Search Algorithm (BSA) is applied to several fed batch fermentation problems and its performance is compared with recent emerging metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and DE. …”
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6
Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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Proceeding Paper -
7
Sensitivity analysis of GA parameters for ECED problem
Published 2023“…Besides the conventional method by using the Lagrange Multiplier several evolutionary computation techniques such as Genetic Algorithm, Particle Swarm Optimisation, Ant Colony and Differential Evolution have been gaining popularity in solving general economic dispatch problems due to their desirable characteristics such as non-gradient dependent and ability to search for global optima. …”
Conference paper -
8
Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach
Published 2018“…Genetic Programming (GP) algorithm is an example of an evolutionary algorithm (EA) in the field of evolutionally computation (EC) and, more broadly, in Artificial Intelligence. …”
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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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10
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…The performance of most metaheuristic algorithms depends on parameters whose settings essentially serve as a key function in determining the quality of the solution and the efficiency of the search. …”
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11
Forecasting solar power generation using evolutionary mating algorithm-deep neural networks
Published 2024“…This paper proposes an integration of recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) in optimizing the weights and biases of deep neural networks (DNN) for forecasting the solar power generation. …”
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Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm
Published 2018“…DE traditionally performs better than other evolutionary algorithms and swarm intelligence techniques in optimization of fed-batch fermentation. …”
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Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity
Published 2018“…On the other hand, an evolutionary algorithm has proven its effectiveness in searching the best feature subsets. …”
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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“…FEP and MCSA are based on the conventional Evolutionary Programming (EP) and Cuckoo Search Algorithm (CSA) with modifications and adjustment to boost up their search ability. …”
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15
Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach
Published 2023“…Genetic Programming (GP) algorithm is an example of an evolutionary algorithm (EA) in the field of evolutionally computation (EC) and, more broadly, in Artificial Intelligence. …”
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Software testing optimization for large systems using agent-based and NSGA-II algorithms
Published 2023“…The multiobjective optimization problem is addressed in this article using a novel evolutionary technique to find a global solution in the Pareto form. …”
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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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The advantages of genetic algorithm and neural networks to forecast air pollution trend in Malaysia: an overview / Mohamad Idham Md Razak … [et al.]
Published 2012“…Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. …”
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Book Section -
19
Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…This diversifies the search for global optimum. The classical benchmark problems and composite benchmark functions from Congress on Evolutionary Computation (CEC) 2005 special session is used for validate SDAA. …”
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Thesis -
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Local Search Based Enhanced Multi-objective Genetic Algorithm of Training Backpropagation Neural Network for Breast Cancer Diagnosis
Published 2017“…Most of multi-objective evolutionary algorithms used NSGA-II due to a good performance in comparison with other multi-objective evolutionary algorithms. …”
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