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Volumn 91, Issue 1, 1998, Pages 83-90

Towards designing artificial neural networks by evolution

Author keywords

Adaptation; Artificial neural networks; Evolution; Evolutionary algorithms; Generalisation; Learning

Indexed keywords


EID: 0002702865     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0096-3003(97)10005-4     Document Type: Article
Times cited : (121)

References (12)
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    • The evolution of connectionist networks
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    • X. Yao, The evolution of connectionist networks, in: T. Dartnall (Ed.), Artificial Intelligence and Creativity, Kluwer Academic Publishers, Dordrecht, 1994, pp. 233-243.
    • (1994) Artificial Intelligence and Creativity , pp. 233-243
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    • An evolutionary algorithm that constructs recurrent neural networks
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    • An empirical study of genetic operators in genetic algorithms
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    • (1993) Microprocessing Microprogramming , vol.38 , pp. 707-714
    • Yao, X.1
  • 10
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    • A population-based learning algorithm which learns both architectures and weights of neural networks
    • Y. Liu, X. Yao, A population-based learning algorithm which learns both architectures and weights of neural networks, Chin. J. Advanced Software Res. 3 (1) (1996) 54-65.
    • (1996) Chin. J. Advanced Software Res. , vol.3 , Issue.1 , pp. 54-65
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  • 11
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    • A new evolutionary system for evolving artificial neural networks
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  • 12
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    • Evolutionary artificial neural networks that learn and generalise well
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    • Yao, X.1    Liu, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.