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Cloud Model Bat Algorithm

Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge r...

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Detalles Bibliográficos
Autores principales: Zhou, Yongquan, Xie, Jian, Li, Liangliang, Ma, Mingzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4055364/
https://www.ncbi.nlm.nih.gov/pubmed/24967425
http://dx.doi.org/10.1155/2014/237102
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author Zhou, Yongquan
Xie, Jian
Li, Liangliang
Ma, Mingzhi
author_facet Zhou, Yongquan
Xie, Jian
Li, Liangliang
Ma, Mingzhi
author_sort Zhou, Yongquan
collection PubMed
description Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization.
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spelling pubmed-40553642014-06-25 Cloud Model Bat Algorithm Zhou, Yongquan Xie, Jian Li, Liangliang Ma, Mingzhi ScientificWorldJournal Research Article Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. Hindawi Publishing Corporation 2014 2014-05-19 /pmc/articles/PMC4055364/ /pubmed/24967425 http://dx.doi.org/10.1155/2014/237102 Text en Copyright © 2014 Yongquan Zhou et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhou, Yongquan
Xie, Jian
Li, Liangliang
Ma, Mingzhi
Cloud Model Bat Algorithm
title Cloud Model Bat Algorithm
title_full Cloud Model Bat Algorithm
title_fullStr Cloud Model Bat Algorithm
title_full_unstemmed Cloud Model Bat Algorithm
title_short Cloud Model Bat Algorithm
title_sort cloud model bat algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4055364/
https://www.ncbi.nlm.nih.gov/pubmed/24967425
http://dx.doi.org/10.1155/2014/237102
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