Dong, D., McAvoy, T.J. (1996) Nonlinear principal component analysis—Based on principal curves and neural networks. Computers & Chemical Engineering, 20. 65-78 doi:10.1016/0098-1354(95)00003-k

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Reference Type	Journal (article/letter/editorial)
Title	Nonlinear principal component analysis—Based on principal curves and neural networks
Journal	Computers & Chemical Engineering
Authors	Dong, D.		Author
Authors	McAvoy, T.J.		Author
Year	1996 (January)	Volume	20
Publisher	Elsevier BV
DOI	doi:10.1016/0098-1354(95)00003-kSearch in ResearchGate
	Generate Citation Formats
Mindat Ref. ID	6605023	Long-form Identifier	mindat:1:5:6605023:6
GUID	0
Full Reference	Dong, D., McAvoy, T.J. (1996) Nonlinear principal component analysis—Based on principal curves and neural networks. Computers & Chemical Engineering, 20. 65-78 doi:10.1016/0098-1354(95)00003-k
Plain Text	Dong, D., McAvoy, T.J. (1996) Nonlinear principal component analysis—Based on principal curves and neural networks. Computers & Chemical Engineering, 20. 65-78 doi:10.1016/0098-1354(95)00003-k
In	(n.d.) Computers & Chemical Engineering Vol. 20. Elsevier BV

	*Qin, S.J., McAvoy, T.J. (1996) Nonlinear FIR modeling via a neural net PLS approach. Computers & Chemical Engineering, 20. 147-159 doi:10.1016/0098-1354(95)00011-p*
	Dunia, Ricardo, Joe Qin, S., Edgar, Thomas F., McAvoy, Thomas J. (1996) Use of principal component analysis for sensor fault identification. Computers & Chemical Engineering, 20. doi:10.1016/0098-1354(96)00128-7
	*Qin, S.J., McAvoy, T.J. (1992) Nonlinear PLS modeling using neural networks. Computers & Chemical Engineering, 16. 379-391 doi:10.1016/0098-1354(92)80055-e*
	*Venkatasubramanian, V., McAvoy, T.J. (1992) Neural network applications in chemical engineering. Computers & Chemical Engineering, 16. doi:10.1016/0098-1354(92)80043-9*
	*Rigopoulos, Apostolos, Arkun, Yaman (1996) Principal components analysis in estimation and control of paper machines. Computers & Chemical Engineering, 20. doi:10.1016/0098-1354(96)00184-6*
	*Heo, Seongmin, Lee, Jay H. (2019) Parallel neural networks for improved nonlinear principal component analysis. Computers & Chemical Engineering, 127. 1-10 doi:10.1016/j.compchemeng.2019.05.011*
	*Bhat, N.V., McAvoy, T.J. (1992) determining model structure for neural models by network stripping. Computers & Chemical Engineering, 16. 271-281 doi:10.1016/0098-1354(92)80047-d*
	*Dong, Dong, McAvoy, Thomas J. (1996) Batch tracking via nonlinear principal component analysis. AIChE Journal, 42 (8). 2199-2208 doi:10.1002/aic.690420810*
	*Tong, Hongwei, Crowe, Cameron M. (1996) Detecting persistent gross errors by sequential analysis of principal components. Computers & Chemical Engineering, 20. doi:10.1016/0098-1354(96)00000-2*
	*Schenker, B., Agarwal, M. (1996) Cross-validated structure selection for neural networks. Computers & Chemical Engineering, 20. 175-186 doi:10.1016/0098-1354(95)00013-r*
	*Bhat, N., McAvoy, T.J. (1990) Use of neural nets for dynamic modeling and control of chemical process systems. Computers & Chemical Engineering, 14. 573-582 doi:10.1016/0098-1354(90)87028-n*

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Dong, D., McAvoy, T.J. (1996) Nonlinear principal component analysis—Based on principal curves and neural networks. Computers & Chemical Engineering, 20. 65-78 doi:10.1016/0098-1354(95)00003-k

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