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Locally Weighted Regression for Desulphurisation Intelligent Decision System Modeling by Hiphung Leung; Yingsong Huang; Changxiu Cao is a Engineering article available to read on EtoBox.

What is Locally Weighted Regression for Desulphurisation Intelligent Decision System Modeling about?

Locally weighted regression (LWR) is a memory-based learning method which performs regression around a point of interest, which is useful for learning the rule of complex phenomenon and system. This paper studies the possibility of using locally weighted regression for modelling an intelligent decision system for desulphurisation in metallurgical process and proposes a hybrid algorithm by combining LWR with Genetic Algorithm (GA). The proposed algorithm proves to be effective and practicable in its application.

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Author

Hiphung Leung; Yingsong Huang; Changxiu Cao

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 1569-190X)

Published

2004

Language

EN

Field

Engineering (Physical Sciences)