A coevolutionary artificial bee colony for training feedforword neural networks

A coevolutionary artificial bee colony (CoABC) trainer based on a hybrid encoding mode is proposed to optimize the network structure and connection weights of a single-hidden layer feedforward network (SLFN). In the proposed CoABC, an integrated population (or colony) with double subpopulations, one...

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Vydáno v:	Neural computing & applications Ročník 37; číslo 27; s. 22649 - 22666
Hlavní autoři:	Zhang, Li, Li, Hong, Gao, Weifeng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.09.2025 Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Bees Classification Coding Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Evolution Genetic algorithms Heuristic methods Image Processing and Computer Vision Neural networks Optimization Probability and Statistics in Computer Science S.I.: Hybrid Approaches to Nature-inspired Optimization Algorithms and Their Applications Saturn Special Issue on Hybrid Approaches to Nature-inspired Optimization Algorithms and Their Applications Swarm intelligence Trainers Training Data classification Structure learning Artificial bee colony Coevolutionary algorithm Parameter optimization Feedforward neural network
ISSN:	0941-0643, 1433-3058
On-line přístup:	Získat plný text
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