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A Cooperative Evolutionary System for Designing Neural Networks
Niu B(牛奔); Zhu YL(朱云龙); Hu KY(胡琨元); Li SF(李素粉); He XX(何小贤)
Department先进制造技术实验室
Conference NameInternational Conference on Intelligent Computing (ICIC)
Conference DateAugust 16-19, 2006
Conference PlaceKunming, China
Author of SourceIEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Sci Fdn China
Source PublicationINTELLIGENT COMPUTING, PART I - INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING, ICIC 2006, PART I
PublisherSPRINGER-VERLAG
Publication PlaceBERLIN
2006
Pages12-21
Indexed ByEI ; CPCI(ISTP)
EI Accession number20064210172591
WOS IDWOS:000278727500002
Contribution Rank1
ISSN0302-9743
ISBN978-3-540-37271-4
AbstractA novel cooperative evolutionary system, i.e., CGPNN, for automatic design artificial neural networks (ANN's) is presented where ANN's structure and parameters are tuned simultaneously. The algorithms used in CGPNN combine genetic algorithm (GA) and particle swarm optimization (PSO) on the basis of a direct encoding scheme. In CGPNN, standard (real-coded) PSO is employed to training ANN's free parameters (weights and bias) and binary-coded GA is used to find optimal ANN's structure. In the simulation part, CGPNN is applied to the predication of tool life. The experimental results show that CGPNN has good accuracy and generalization ability in comparison with other algorithms.
Language英语
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/8153
Collection工业信息学研究室_先进制造技术研究室
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Graduate School, Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Niu B,Zhu YL,Hu KY,et al. A Cooperative Evolutionary System for Designing Neural Networks[C]//IEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Sci Fdn China. BERLIN:SPRINGER-VERLAG,2006:12-21.
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