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Volumn 22, Issue SUPPL.1, 1998, Pages

Adaptive hybrid neural models for process control

Author keywords

[No Author keywords available]

Indexed keywords


EID: 0008828229     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0098-1354(98)00197-5     Document Type: Article
Times cited : (25)

References (12)
  • 1
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    • (1990) Int.J.Control , vol.51 , pp. 6
    • Chen, S.1    Cowan, C.2    Billings, S.3    Grant, P.4
  • 2
    • 0031176171 scopus 로고    scopus 로고
    • Identification and optimizing control of a rougher flotation circuit using an adaptable hybrid-neural model
    • Cubillos F. and Lima E., 1997, Identification and optimizing control of a rougher flotation circuit using an adaptable hybrid-neural model. Minerals Engineering, 10, 707-721.
    • (1997) Minerals Engineering , vol.10 , pp. 707-721
    • Cubillos, F.1    Lima, E.2
  • 5
    • 0026617161 scopus 로고
    • Model-based control of mineral processing operations
    • Herbst J. Pate W. and Oblad E., 1992.,Model-based control of mineral processing operations, Powder Technology, 69, 21-32.
    • (1992) Powder Technology , vol.69 , pp. 21-32
    • Herbst, J.1    Pate, W.2    Oblad, E.3
  • 6
    • 0025536559 scopus 로고
    • Neural network modeling and an extended DMC algorithm to control non-linear system
    • Hernandez E. and Arknn Y., 1990, Neural network modeling and an extended DMC algorithm to control non-linear system, Proc.ACC, 1990, 2454-2459.
    • (1990) Proc.ACC , vol.1990 , pp. 2454-2459
    • Hernandez, E.1    Arknn, Y.2
  • 7
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • Hornik K. Stinchcombe M. and White H., 1989, Multilayer feedforward networks are universal approximators, Neural Networks,2, 359-366.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 8
    • 0027007477 scopus 로고
    • Non linear Internal Model Control strategy for neural networks models
    • Nahas E. Henson M. and Seborg D., 1992, Non linear Internal Model Control strategy for neural networks models, Computers Chem. Engng., 16,2, 1911-1925
    • (1992) Computers Chem. Engng. , vol.16 , Issue.2 , pp. 1911-1925
    • Nahas, E.1    Henson, M.2    Seborg, D.3
  • 9
    • 0043243991 scopus 로고
    • A fast procedure for training neural networks
    • Peel C. Willis M. and Tham M., 1992, A fast procedure for training neural networks, J.Proc.Control, 2,4.
    • (1992) J.Proc.Control , vol.2 , pp. 4
    • Peel, C.1    Willis, M.2    Tham, M.3
  • 10
    • 0026403834 scopus 로고
    • Direct and indirect model based control using artificial neural networks
    • Psichogios D and Ungar L.,1991, Direct and indirect model based control using artificial neural networks, Ind.Eng.Chem.Res, 30, 2564-2573.
    • (1991) Ind.Eng.Chem.Res , vol.30 , pp. 2564-2573
    • Psichogios, D.1    Ungar, L.2
  • 11
    • 0026806616 scopus 로고
    • A hybrid neural network first-principles approach to process modeling
    • Psichogios D. and Ungar L.,1992., A hybrid neural network first-principles approach to process modeling, AICHE J., 36, 1499.
    • (1992) AICHE J. , vol.36 , pp. 1499
    • Psichogios, D.1    Ungar, L.2
  • 12
    • 0028484335 scopus 로고
    • Modeling chemical processes using prior knowledge and neural networks
    • Thompson M. and Kramer M., 1994, Modeling chemical processes using prior knowledge and neural networks,AICHEJ.,40, 132.
    • (1994) AICHEJ. , vol.40 , pp. 132
    • Thompson, M.1    Kramer, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.