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Volumn 6840 LNBI, Issue , 2011, Pages 699-704

An improved extreme learning machine based on particle swarm optimization

Author keywords

Extreme learning machine; generalization performance; particle swarm optimization

Indexed keywords

EXTREME LEARNING MACHINE; GENERALIZATION PERFORMANCE; GENERALIZED INVERSE; HIDDEN NEURONS; INPUT WEIGHTS; MODIFIED PARTICLE SWARM OPTIMIZATION; MOORE-PENROSE; PARTICLE SWARM; ROOT MEAN SQUARED ERRORS;

EID: 84855691741     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24553-4_92     Document Type: Conference Paper
Times cited : (21)

References (10)
  • 9
    • 9144229588 scopus 로고    scopus 로고
    • A hierarchical method for finding optimal architecture and weights using evolutionary least square based learning
    • Ghosh, R., Verma, B.: A hierarchical method for finding optimal architecture and weights using evolutionary least square based learning. International Journal of Neural Systems 12(1), 13-24 (2003)
    • (2003) International Journal of Neural Systems , vol.12 , Issue.1 , pp. 13-24
    • Ghosh, R.1    Verma, B.2
  • 10
    • 0032028728 scopus 로고    scopus 로고
    • The sample complexity of pattern classification with neural networks: The size of the weights is more important than the size of the network
    • Bartlett, P.L.: The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network. IEEE Trans. Inform. Theory 44(2), 525-536 (1998)
    • (1998) IEEE Trans. Inform. Theory , vol.44 , Issue.2 , pp. 525-536
    • Bartlett, P.L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.