[1] Hornik, K., Stinchcombe, M., White, H., "Multilayer feedforward networks are universal
approximators", Neural Networks, 2, 359-366 (1989).
[2] Hornik, K., Stinchcombe, M., White, H., "Universal approximation of an unknown mapping
and its derivatives using multilayer feedforward networks", Neural Networks,
[3] , 551-560 (1990).3.Joerding, W.H., Meador, J.L, "Encoding a priori information in
feedforward networks", Neural Networks, 4, 847-862 (1991).
[4] Michael, L.T., Mark, A.K., "Modeling chemical processes using prior knowledge and
neural networks", AIChE, 40(8), 1328-1340 (1994).
[5] Chen, C.-W., Chen, D.-Z., Ye, X.-Q., Hu, S.-X, "Feedforward networks based on prior
knowledge and its application in modeling the true boiling point curve of the crude oil",J.
Chem. Eng. Chinese Univ., 15 (4), 351-356 (2001). (in Chinese)
[6] Chen, C.-W., Chen, D.-Z., "Prior-knowledge-based feedforward network simulation of true
boiling point curve of crude oil", Computers and Chemistry, 25 (6), 541-550 (2001).
[7] Hu, S.-X, "Study on the vapor-liquid equilibrium calculation of the distilled component
of crude oil using spline function", J. East China Petro. Inst., 1, 1-18 (1983). (in
Chinese)
[8] Bazaraa, M.S., Shetty, C.M., Nonlinear Programming:Theory and Algorithms, John Wiley &
Sons, Washington DC(1979)
[9] Avriel, M., Nonlinear Programming: Analysis and Methods, PRENTICE-HALL, INC, New
Jersey(1976).
[10] Martens, H.A., Pierre, Dardenne, "Validation and verification of regression in small
data sets", Chemometrics and Intelligent Laboratory Systems, 44, 99-121 (1998).
[11] Martens, H.A., Naes, T, Multivariate Calibration, Wiley,Chichester, UK (1989).
[12] A0KI, M., Introduction to Optimization Techniques: Fundamentals and Applications of
Nonlinear Programming,Collier-Macmillan, London (1971).
[13] Hagan, M.T., Menhaj, M., "Training feedforward networks with the Marquardt algorithm",
IEEE Transactions on Neural Networks, 5 (6), 989-993 (1994). |
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