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An improved PSO-based ANN with simulated annealing technique
Yi, D; Ge, XR
2005
Source PublicationNEUROCOMPUTING
ISSN0925-2312
Volume63Issue:-Pages:527-533
Abstract

This paper presents a modified particle swarm optimization (PSO) with simulated annealing (SA) technique. An improved PSO-based artificial neural network (ANN) is developed. The results show that the proposed SAPSO-based ANN has a better ability to escape from a local optimum and is more effective than the conventional PSO-based ANN. (C) 2004 Elsevier B.V. All rights reserved.

KeywordArtificial Neural Networks Particle Swarm Optimization Simulated Annealing
DOI10.1016/j.neucom.2004.07.002
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000226705700026
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:135[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://119.78.100.198/handle/2S6PX9GI/3124
Collection岩土力学所知识全产出_期刊论文
AffiliationShanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn; Chinese Acad Sci, Inst Rock & Soil Mech
Recommended Citation
GB/T 7714
Yi, D,Ge, XR. An improved PSO-based ANN with simulated annealing technique[J]. NEUROCOMPUTING,2005,63(-):527-533.
APA Yi, D,&Ge, XR.(2005).An improved PSO-based ANN with simulated annealing technique.NEUROCOMPUTING,63(-),527-533.
MLA Yi, D,et al."An improved PSO-based ANN with simulated annealing technique".NEUROCOMPUTING 63.-(2005):527-533.
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