Development of a robust hybrid estimator using partial least squares regression and artificial neural networks.

Measurement difficulty is one of the process control issues arising from the complexity and the lack of online measurement devices. One of the alternative solutions to deal with the problem is inferential estimation where secondary variables, such as temperature and pressure are used to predict the...

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Podrobná bibliografie
Hlavní autoři:	Ahmad, Arshad, Lim, Wan Piang
Médium:	Článek
Jazyk:	English
Vydáno:	Universiti Malaysia Sabah 2003
Témata:	T Technology (General)
On-line přístup:	http://eprints.utm.my/8024/1/ArshadAhmad2003_DevelopmentOfARobustHybridEstimator.pdf

Development of a robust hybrid estimator using partial least squares regression and artificial neural networks / Autor Arshad Ahmad, 1963-, Lim, Wan Piang, Proceedings of the International Conference on Chemical and Bioprocess Engineering (2003 : Universiti Malaysia Sabah, Kota Kinabalu)

Vydáno 2003

Development of a robust hybrid estimator using partial least squares regression and artificial neural networks.

Development of a robust hybrid estimator using partial least squares regression and artificial neural networks / Autor Arshad Ahmad, 1963-, Lim, Wan Piang, Proceedings of the International Conference on Chemical and Bioprocess Engineering (2003 : Universiti Malaysia Sabah, Kota Kinabalu)

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