シャ　キンカ   Jinhua She   佘　錦華    所属   工学部 機械工学科    職種   教授
言語種別	英語
発行・発表の年月	2017/07
形態種別	国際会議論文
査読	査読あり
標題	An Improved-WM Method Based on Optimization of Centers of Output Fuzzy Subsets for Fuzzy Rules
執筆形態	共著
掲載誌名	The 20th World Congress of the International Federation of Automatic Control (IFAC 2017)
掲載区分	国外
出版社・発行元	The International Federation of Automatic Control
巻・号・頁	pp.7630-7635
担当範囲	ALL
著者・共著者	Yali Jin, Weihua Cao, Min Wu, Jinhua She, and Yan Yuan
概要	The generation of fuzzy rules from samples is significant for fuzzy modelling. To improve the robustness of Wang-Mendel (WM) method, an improved WM method to extract fuzzy rules from all the regularized sample data was proposed. However, the accuracy of the model with this method is degraded for the conflicting rules with small difference between support degrees. And the output subsets can only be chosen from the pre-defined ones. To solve these problems, we develop an improved-WM method based on optimization of centers of output fuzzy subsets for fuzzy rules (COiWM). This method adopts the fuzzy c-means (FCM) clustering algorithm to divide the input and output spaces, and the improved WM method which replaces the original data by regularized data is used to calculate the support degrees. Then the support degrees are used as weights to optimize the centers of output fuzzy subsets with a method of weighted averages, so as to enhance the accuracy of a fuzzy model. Experimental results of a case study on short term daily maximum electric load forecasting prove that our proposed method enhances the accuracy of a fuzzy model.
外部リンクURL	https://www.sciencedirect.com/science/article/pii/S2405896317320864