Dimensionality Reduction with Input Training Neural Network and Its Application in Chemical Process Modelling
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[1] Teng Hu. Prediction of Process Trends Based on Neural Networks , 2002 .
[2] A. J. Morris,et al. Wavelets and non-linear principal components analysis for process monitoring , 1999 .
[3] D. Kunzru,et al. Modeling of naphtha pyrolysis , 1985 .
[4] Qunxiong Zhu,et al. Multiscale Nonlinear Principal Component Analysis (NLPCA) and Its Application for Chemical Process Monitoring , 2005 .
[5] I. Jolliffe. Principal Component Analysis and Factor Analysis , 1986 .
[6] Anders Krogh,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[7] R. Palmer,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[8] M. Kramer. Nonlinear principal component analysis using autoassociative neural networks , 1991 .
[9] Xu Yong-mao. A Soft-sensing Approach to On-line Predict the Yields of Industrial Pyrolysis Furnace Based on PCA-RBF Neural Networks , 2001 .
[10] Shufeng Tan,et al. Reducing data dimensionality through optimizing neural network inputs , 1995 .
[11] A. J. Morris,et al. Non-linear principal components analysis for process fault detection , 1998 .
[12] T. McAvoy,et al. Nonlinear principal component analysis—Based on principal curves and neural networks , 1996 .