Please use this identifier to cite or link to this item:
Title: An enhanced just-in-time learning methodology for process modeling
Authors: Cheng, C.
Hashimoto, Y.
Chiu, M.-S. 
Issue Date: 2004
Citation: Cheng, C.,Hashimoto, Y.,Chiu, M.-S. (2004). An enhanced just-in-time learning methodology for process modeling. 2004 5th Asian Control Conference 3 : 2073-2078. ScholarBank@NUS Repository.
Abstract: A new just-in-time learning methodology for nonlinear process modeling is developed in this paper. In the proposed method, both distance measure and angle measure are used to evaluate the similarity between data, which is not exploited in the conventional methods. In addition, parametric stability constraints are incorporated into the proposed method to address the stability of local models. Furthermore, a new procedure of selecting the relevant data set is proposed. The proposed methodology is illustrated by a case study of modeling a polymerization reactor. The adaptive ability of the just-in-time learning is also evaluated.
Source Title: 2004 5th Asian Control Conference
ISBN: 0780388739
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on Oct 14, 2021

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.