An evolutionary swarm intelligence optimizer based on probabilistic distribution

In this study, we propose a novel approach to balance exploitation and exploration. The proposed approach is the Evolutionary Swarm Intelligence (ESI) optimizer, which combines an exploration-biased strategy with an exploitation-biased operator. The algorithm is built based on the collective behavio...

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Veröffentlicht in:	Neural computing & applications Jg. 37; H. 27; S. 22387 - 22399
Hauptverfasser:	Yang, Yifei, Yang, Haichuan, Li, Haotian, Tang, Zheng, Gao, Shangce
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.09.2025 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Biological activity Biological evolution Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Evolution Exploitation Genes Genetic algorithms Image Processing and Computer Vision Manual workers Optimization Performance evaluation Probability and Statistics in Computer Science S.I.: Hybrid Approaches to Nature-inspired Optimization Algorithms and Their Applications Sociology Special Issue on Hybrid Approaches to Nature-inspired Optimization Algorithms and Their Applications Swarm intelligence Swarm intelligence Dendritic neuron model Meta-heuristic algorithms Genetic algorithm Exploitation and exploration
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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