期刊
SIMULATION MODELLING PRACTICE AND THEORY
卷 12, 期 6, 页码 413-423出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.simpat.2004.06.002
关键词
locally weighted regression; model fitting; parameter fitting; intelligent decision system; genetic algorithm; optimisation
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. (C) 2004 Elsevier B.V. All rights reserved.
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