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Volumn , Issue , 2005, Pages 35-42

An application of non-linear programming to train Recurrent Neural Networks in Time Series Prediction problems

Author keywords

Non linear programming; Recurrent Neural Networks; Time Series Prediction

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BIO-INSPIRED; COMPLEX PROBLEMS; ELMAN RECURRENT NEURAL NETWORK; EVOLUTIONARY TECHNIQUES; EXPERIMENTAL SECTION; LIFE-TIMES; LOCAL SOLUTION; SUITABLE SOLUTIONS; TIME SERIES PREDICTION; TRAINING ALGORITHMS;

EID: 33646672300     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (14)

References (14)
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  • 2
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    • Zhu, C.1    Byrd, R.H.2    Nocedal, J.3
  • 3
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    • A comparative study of evolutionary algorithms for training elman recurrent neural networks to predict the autonomous indebtedness
    • Porto, Portugal
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    • (2004) Proc. ICEIS , pp. 457-461
    • Cuéllar, M.P.1    Delgado, M.2    Pegalajar, M.C.3
  • 6
    • 0028543366 scopus 로고
    • Training FeedForward networks with the Marquardt algorithm
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    • Hagan, M.T.1    Menhaj, M.B.2
  • 7
    • 0037239496 scopus 로고    scopus 로고
    • Recurrent neural networks for time series classification
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    • Hüsken, M.1    Stagge, P.2
  • 8
    • 0001362410 scopus 로고
    • The Levenberg-Marquardt algorithm: Implementation and theory
    • Edited by G. A. Watson, SpringerVerlag
    • More, J. J. 1977. The Levenberg-Marquardt algorithm: Implementation and theory. Lecture notes in mathematics, Edited by G. A. Watson, SpringerVerlag.
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    • More, J.J.1
  • 10
    • 1842555205 scopus 로고    scopus 로고
    • Multilayer Neural Networks: An experimental evaluation of on-line training methods
    • R. Martí, A. El-Fallahi. 2002. Multilayer Neural Networks: An experimental evaluation of on-line training methods. Computers and Operations Research 31, pp. 1491-1513.
    • (2002) Computers and Operations Research , vol.31 , pp. 1491-1513
    • Martí, R.1    El-Fallahi, A.2
  • 11
    • 0142154961 scopus 로고    scopus 로고
    • Recurrent radial basis fuction network for time seties prediction
    • Ryad Zemomi, Daniel Racaceanu, Nouredalime Zerhonn. 2003. Recurrent Radial Basis fuction network for Time Seties prediction, Engineering appl. Of Artificial Intelligence, vol. 16, no. 5-6, pp. 453-463.
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    • Zemomi, R.1    Racaceanu, D.2    Zerhonn, N.3
  • 13
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    • An efficient gradient-based algorithm for on-line training of recurrent network trajectories
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    • Williams, R.J.1    Peng, J.2
  • 14
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.