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Volumn 7, Issue , 2009, Pages

A neural network approach for identification and modeling of delayed coking plant

Author keywords

Artificial neural network; Delayed coking unit; Refinery modeling

Indexed keywords

COKING; NEURAL NETWORKS;

EID: 67650471205     PISSN: None     EISSN: 15426580     Source Type: Journal    
DOI: 10.2202/1542-6580.1832     Document Type: Article
Times cited : (16)

References (8)
  • 1
    • 0034149159 scopus 로고    scopus 로고
    • Predicting the effect of feedstock on product yields and properties of the FCC process, PP
    • Al-Enezi G. and A. Elkamel, Predicting the effect of feedstock on product yields and properties of the FCC process, 2000, Petroleum Science and Technology, 18(3&4), PP. 407-428.
    • (2000) Petroleum Science and Technology , vol.18 , Issue.3-4 , pp. 407-428
    • Al-Enezi, G.1    Elkamel, A.2
  • 5
    • 84869364535 scopus 로고    scopus 로고
    • Matlab neural network toolbox
    • Matlab neural network toolbox, www.mathwork.Com, 2006.
    • (2006)
  • 6
    • 67650456024 scopus 로고    scopus 로고
    • Michalopoulos, J., S. Papadokenstadakis, G. Arampatzis, and A. Lygeres, Modeling of an industrial fluid catalytic cracking unit using neural networks, 2001, Trans. IChemE.,
    • Michalopoulos, J., S. Papadokenstadakis, G. Arampatzis, and A. Lygeres, Modeling of an industrial fluid catalytic cracking unit using neural networks, 2001, Trans. IChemE.,
  • 8
    • 33845788092 scopus 로고    scopus 로고
    • Zahedi,G., H. Fgaier, AJahanmiri and G.Al-Enezi, Identification and evaluation of hydrotreater plant, 2005, Pet. Sci. and Tech., 24:1447-1456.
    • Zahedi,G., H. Fgaier, AJahanmiri and G.Al-Enezi, Identification and evaluation of hydrotreater plant, 2005, Pet. Sci. and Tech., 24:1447-1456.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.