A soft-sensing approach to on-line predict the yields of industrial pyrolysis furnace based on PCA-RBF neural networks

Xitong Fangzhen Xuebao / Journal of System Simulation

Volumn 13, Issue SUPPL., 2001, Pages 196-197

  Yang, Er Fu ^a   Zhou, Qiang ^a   Hu, Yi Feng ^a   Xu, Yong Mao ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

Ethylene process; Neural networks; Principal component analysis(PCA); Process modeling; Pyrolysis furnace; Soft sensing

Indexed keywords

EID: 4444379880     PISSN: 1004731X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (7)

1. Chen S, Cowan C F N, Grant P M. Orthogonal least squares learning algorithm for radial basis function networks [J]. IEEE Transactions on Neural Networks, March 1991, 2 (2): 302-309.
2. Dente M, et al. Detailed prediction of olefin yields from hydrocarbon pyrolysis through a fundamental simulation model (SPYRO) [J]. Computers & Chemical Engineering, 1979, (13): 61-75.
3. Kumar P, Kunzru D. Modeling of naphtha pyrolysis [J]. Ind Eng Chem Process Des Dev, 1985, 24(3): 774-782.