A Study of an Modeling Method of T-S fuzzy System Based on Moving Fuzzy Reasoning and Its Application
November 08, 2015 Β· Declared Dead Β· π arXiv.org
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Authors
Son-Il Kwak, Gang Choe, In-Song Kim, Gyong-Ho Jo, Chol-Jun Hwang
arXiv ID
1511.02432
Category
cs.AI: Artificial Intelligence
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
To improve the effectiveness of the fuzzy identification, a structure identification method based on moving rate is proposed for T-S fuzzy model. The proposed method is called "T-S modeling (or T-S fuzzy identification method) based on moving rate". First, to improve the shortcomings of existing fuzzy reasoning methods based on matching degree, the moving rates for s-type, z-type and trapezoidal membership functions of T-S fuzzy model were defined. Then, the differences between proposed moving rate and existing matching degree were explained. Next, the identification method based on moving rate is proposed for T-S model. Finally, the proposed identification method is applied to the fuzzy modeling for the precipitation forecast and security situation prediction. Test results show that the proposed method significantly improves the effectiveness of fuzzy identification.
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