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Volumn 8, Issue 3, 2009, Pages 145-155

Modelling of continuous stirred tank reactor using artificial intelligence techniques

Author keywords

CSTR; Fuzzy; Modelling; Neural networks; Neuro fuzzy

Indexed keywords


EID: 69949112704     PISSN: 17264529     EISSN: None     Source Type: Journal    
DOI: 10.2507/IJSIMM08(3)2.128     Document Type: Article
Times cited : (10)

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  • 3
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    • Nauck, D. (1994). Fuzzy neuro systems: An overview, Kruse, R.; Gebhardt, J.; Palm, R. (Editors), Fuzzy Systems in Computer Science, 91-107
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  • 8
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    • ANFIS: Adaptive-Network based fuzzy inference system
    • Jang, J. (1993). ANFIS: Adaptive-Network Based Fuzzy Inference System, IEEE Trans. on Systems, Man and Cybernetics, Vol. 23, No. 3, 665-685
    • (1993) IEEE Trans. on Systems, Man and Cybernetics , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.1
  • 9
    • 0029273384 scopus 로고
    • Neuro-fuzzy modeling and control
    • Jang, J.; Sun, C. T. (1995). Neuro-Fuzzy Modeling and Control, IEEE Proc, Vol. 83, No. 3, 378-406
    • (1995) IEEE Proc. , vol.83 , Issue.3 , pp. 378-406
    • Jang, J.1    Sun, C.T.2
  • 10
    • 0030385720 scopus 로고    scopus 로고
    • Input selection for ANFIS learning
    • Jang, J. (1996). Input Selection for ANFIS Learning, IEEE Fuzzy Systems, 1493-1499
    • (1996) IEEE fuzzy Systems , pp. 1493-1499
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    • Neuro-fuzzy modeling for dynamic system identification
    • Jang, J. (1996). Neuro-Fuzzy Modeling for Dynamic System Identification, IEEE Fuzzy Systems Symposium, 320-325
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  • 13
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    • Computationally efficient neural predictive control based on a feedforward architecture
    • Kuure-Kinsey, M.; Cutright, R.; Bequette, B. W. (2006). Computationally efficient neural predictive control based on a feedforward architecture, Ind. Eng. Chem. Res., Vol. 45, No. 25, 8575-8582
    • (2006) Ind. Eng. Chem. Res. , vol.45 , Issue.25 , pp. 8575-8582
    • Kinsey, K.M.1    Cutright, R.2    Bequette, B.W.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.