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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Design of Interpretable and Accurate Fuzzy Models from Data
verfasst von : Zong-yi Xing, Yong Zhang, Li-min Jia, Wei-li Hu
Erschienen in: Fuzzy Systems and Knowledge Discovery
Verlag: Springer Berlin Heidelberg
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An approach to identify data-driven interpretable and accurate fuzzy models is presented in this paper. Firstly, Gustafson-Kessel fuzzy clustering algorithm is used to identify initial fuzzy model, and cluster validity indices are adopted to determine the number of rules. Secondly, orthogonal least square method and similarity measure of fuzzy sets are utilized to reduce the initial fuzzy model and improve its interpretability. Thirdly, constraint Levenberg-Marquardt algorithm is used to optimize the reduced fuzzy model to improve its accuracy. The proposed approach is applied to PH neutralization process, and results show its validity.