RIME: A physics-based optimization

Neurocomputing, Journal Year: 2023, Volume and Issue: 532, P. 183 - 214

Published: Feb. 13, 2023

Language: Английский

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Parrot optimizer: Algorithm and applications to medical problems

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 172, P. 108064 - 108064

Published: Feb. 24, 2024

Language: Английский

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Multilevel threshold image segmentation for COVID-19 chest radiography: A framework using horizontal and vertical multiverse optimization

Computers in Biology and Medicine, Journal Year: 2022, Volume and Issue: 146, P. 105618 - 105618

Published: May 18, 2022

Language: Английский

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Simulated annealing-based dynamic step shuffled frog leaping algorithm: Optimal performance design and feature selection

Neurocomputing, Journal Year: 2022, Volume and Issue: 503, P. 325 - 362

Published: June 28, 2022

Language: Английский

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Human Evolutionary Optimization Algorithm

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 241, P. 122638 - 122638

Published: Nov. 16, 2023

Language: Английский

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Hierarchical Harris hawks optimizer for feature selection

Journal of Advanced Research, Journal Year: 2023, Volume and Issue: 53, P. 261 - 278

Published: Jan. 20, 2023

Feature selection is a typical NP-hard problem. The main methods include filter, wrapper-based, and embedded methods. Because of its characteristics, the wrapper method must swarm intelligence algorithm, performance in feature closely related to algorithm's quality. Therefore, it essential choose design suitable algorithm improve based on wrapper. Harris hawks optimization (HHO) superb approach that has just been introduced. It high convergence rate powerful global search capability but an unsatisfactory effect dimensional problems or complex problems. we introduced hierarchy HHO's ability deal with selection. To make obtain good accuracy fewer features run faster selection, improved HHO named EHHO. On 30 UCI datasets, (EHHO) can achieve very classification less running time features. We first conducted extensive experiments 23 classical benchmark functions compared EHHO many state-of-the-art metaheuristic algorithms. Then transform into binary (bEHHO) through conversion function verify extraction data sets. Experiments show better speed minimum than other peers. At same time, HHO, significantly weakness dealing functions. Moreover, datasets repository, bEHHO comparative Compared original bHHO, excellent also bHHO time.

Language: Английский

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Random following ant colony optimization: Continuous and binary variants for global optimization and feature selection

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 144, P. 110513 - 110513

Published: June 15, 2023

Language: Английский

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An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 213, P. 119041 - 119041

Published: Oct. 17, 2022

Language: Английский

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Gaussian kernel probability-driven slime mould algorithm with new movement mechanism for multi-level image segmentation

Measurement, Journal Year: 2022, Volume and Issue: 192, P. 110884 - 110884

Published: Feb. 14, 2022

Language: Английский

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Multi-level threshold segmentation framework for breast cancer images using enhanced differential evolution

Biomedical Signal Processing and Control, Journal Year: 2022, Volume and Issue: 80, P. 104373 - 104373

Published: Nov. 14, 2022

Language: Английский

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