Design of interpretable and accurate fuzzy models from data

Authors:
Zong-yi Xing;Yong Zhang;Li-min Jia;Wei-li Hu
Affiliations:
Nanjing University of Science and Technology, Nanjing, China;Nanjing University of Science and Technology, Nanjing, China;Beijing Jiaotong University, Beijing, China;Nanjing University of Science and Technology, Nanjing, China
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Year:
2005

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Abstract

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.