Optimization of CSO algorithm based on adaptive inertia weight coefficient

Autor:	Dongnan Suo
Rok vydání:	2021
Předmět:	History Computer science Control theory media_common.quotation_subject Weight coefficient Inertia Computer Science Applications Education media_common
Zdroj:	Journal of Physics: Conference Series. 2078:012009
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/2078/1/012009
Popis:	The traditional CSO algorithm is easy to fall into local extremum in optimization. In this paper, a CSO algorithm based on weight coefficient is proposed. In the CSO algorithm, the inertia weight coefficient is introduced into the hen position formula, and the learning factor influenced by the rooster is added to the chick position formula. Finally, using the idea of heredity, individuals with excellent fitness value are selected for crossover and mutation with a certain probability. Through the simulation comparison of five typical test functions, the simulation results show that the improved CSO algorithm can avoid local optimization, strengthen the global extreme value search ability, and improve the convergence speed and accuracy range of the algorithm.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0b07132f5bc3dae02e4edfda6aed88fd https://doi.org/10.1088/1742-6596/2078/1/012009 Zobrazit plný text záznamu