Nonlinear System Identification with Selective Recursive Gaussian Process Models-Reference-Cited by-同舟云学术

Nonlinear System Identification with Selective Recursive Gaussian Process Models

Published:2013-12-16 Issue:51 Volume:52 Page:18276-18286
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Chan Lester Lik Teck¹,Liu Yi²,Chen Junghui¹

Affiliation:

1. R&D Center for Membrane Technology, Department of Chemical Engineering, Chung-Yuan Christian University, Chung-Li, Taiwan 320, Republic of China

2. Engineering Research Center of Process Equipment and Remanufacturing, Ministry of Education, Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, P. R. China

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ie4031538

Reference28 articles.

1. Four Encounters with System Identification

2. Vincent, V.Nonlinear system identification: A state-space approach. Ph.D. Thesis,University of Twente, 2002.

3. Accounts of Experiences in the Application of Artificial Neural Networks in Chemical Engineering

4. Boyle, P.Gaussian processes for regression and optimization. Ph.D. Thesis,Victoria University of Wellington, 2007.

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