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Volumn 1, Issue , 2001, Pages 523-528

Recurrent neuro-fuzzy networks for the modelling and optimal control of batch processes

Author keywords

[No Author keywords available]

Indexed keywords

MEMBERSHIP FUNCTIONS; NONLINEAR SYSTEMS; OPTIMAL CONTROL SYSTEMS; PROBLEM SOLVING;

EID: 0035792672     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (2)

References (13)
  • 1
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    • Takagi, T.1    Sugeno, M.2
  • 2
    • 50649125497 scopus 로고
    • Constructing NARMAX models using ARMAX models
    • T. A. Johansen, and B. A. Foss, "Constructing NARMAX models using ARMAX models", Int. J. Control, Vol.58, 1993, pp1125-1153.
    • (1993) Int. J. Control , vol.58 , pp. 1125-1153
    • Johansen, T.A.1    Foss, B.A.2
  • 5
    • 0001146813 scopus 로고    scopus 로고
    • Process modelling and fault diagnosis using fuzzy neural networks
    • J. Zhang, and A. J. Morris, "Process modelling and fault diagnosis using fuzzy neural networks", Fuzzy Sets and Systems, Vol.79, 1996, pp127-140.
    • (1996) Fuzzy Sets and Systems , vol.79 , pp. 127-140
    • Zhang, J.1    Morris, A.J.2
  • 6
    • 0033098832 scopus 로고    scopus 로고
    • Recurrent neuro-fuzzy networks for nonlinear process modeling
    • J. Zhang, and A. J. Morris, "Recurrent neuro-fuzzy networks for nonlinear process modeling", IEEE Transactions on Neural Networks, Vol.10, 1999, pp313-326.
    • (1999) IEEE Transactions on Neural Networks , vol.10 , pp. 313-326
    • Zhang, J.1    Morris, A.J.2
  • 7
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • In: D. E. Rumelhart, J. L. McClelland. (Eds); MIT Press
    • D. E. Rumelhart, G.E. Hinton, and R. J. Williams, "Learning internal representations by error propagation", In: D. E. Rumelhart, J. L. McClelland. (Eds), Parallel Distributed Processing, MIT Press, 1986.
    • (1986) Parallel Distributed Processing
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 8
    • 0025403609 scopus 로고
    • Improvement of the back-propagation algorithm for training neural networks
    • J. A. Leonard, and M. A. Kramer, "Improvement of the back-propagation algorithm for training neural networks", Computers & Chemical Engineering, Vol.14, 1990, pp337-341.
    • (1990) Computers & Chemical Engineering , vol.14 , pp. 337-341
    • Leonard, J.A.1    Kramer, M.A.2
  • 9
    • 0000169232 scopus 로고
    • An algorithm for least squares estimation of nonlinear parameters
    • D. Marquardt, "An algorithm for least squares estimation of nonlinear parameters", SIAM J. Appl. Math., Vol.11, 1963, pp431-441.
    • (1963) SIAM J. Appl. Math. , vol.11 , pp. 431-441
    • Marquardt, D.1
  • 10
    • 0033083995 scopus 로고    scopus 로고
    • On the improvement of the real time recurrent learning algorithm for recurrent neural networks
    • M. W. Mak, K. W. Ku, and Y. L. Lu, "On the improvement of the real time recurrent learning algorithm for recurrent neural networks", Neurocomputing, Vol.24, 1999, pp13-36
    • (1999) Neurocomputing , vol.24 , pp. 13-36
    • Mak, M.W.1    Ku, K.W.2    Lu, Y.L.3
  • 11
    • 0025503558 scopus 로고
    • Backpropagation through time: What it does and how to do it
    • P. J. Werbos, "Backpropagation through time: what it does and how to do it", Proceedings of IEEE, Vol.78, 1990, pp1550-1560.
    • (1990) Proceedings of IEEE , vol.78 , pp. 1550-1560
    • Werbos, P.J.1
  • 13
    • 0028378098 scopus 로고
    • The composition and validation of heterogeneous control laws
    • B. Kuipers, and K. Astrom, "The composition and validation of heterogeneous control laws", Automatica, Vol.30, 1994, pp233-249.
    • (1994) Automatica , vol.30 , pp. 233-249
    • Kuipers, B.1    Astrom, K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.