Search Results - adoption ((two different) OR (a difference)) ((evolution algorithm) OR (evolutionary algorithm))
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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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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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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
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Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…Harmony Search (HS) algorithm has been extensively adopted in the literature to address optimization problems in many different fields, such as industrial design, civil engineering, electrical and mechanical engineering problems. …”
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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS_Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS_Ch may offer a useful way for reliable enhancement of the detection of different emotional states of the brain regions.…”
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A comparative study for parameter selection in online auctions
Published 2009“…In this work, three different models of genetic algorithms are considered. …”
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Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme
Published 2014“…The percentage difference is 2.1%,compared with the full feedback method, with only 0.5% degradation. …”
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers
Published 2021“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Delay-Aware Energy-Efficient Joint Power Control and Mode Selection in Device-to-Device Communications for FREEDM Systems in Smart Grids
Published 2024“…We adopt a D2D-assisted relaying framework to assist links that meet poor channel conditions in order to increase the data rate of intelligent energy management devices with large size report. …”
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Optimal coordination of overcurrent relay protection using evolutionary programming / Noor Shah Rizal Abdul Manap
Published 2018“…Therefore, this research employed a metaheuristic optimization for Evolutionary Programming (EP) to find the optimum time for optimization overcurrent protection relay in radial distribution system. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…WISDM consists of six different types physical activity, while PAMAP2 covers eighteen activities comprising various simple and complex activities. …”
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Computational methods for self-assembly of DNA nanostructures / Ong Hui San
Published 2016“…In this study, the concept of Tetris game to facilitate DNA nanostructures fabrication was adapted; whereby different DNA Tetris shapes were used to form complex 2D DNA structures. …”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems
Published 2022“…Gradient-based Mutation MRFO (GbM-MRFO) is derived from basic strategy of MRFO and synergized with the Gradient-based Mutation strategy. MRFO is a recently new introduced algorithm that consists of strategy of foraging adopted by Manta Ray while Gradient-based Mutation (GbM) is a feasibility-and solution repair strategy adopted from ϵ-Matrix-Adaptation Evolution Strategy (ϵ-MAES). …”
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