Parameter Tuning in Adaptive Fuzzy Regression

• RYOKE Mina

  School of Knowledge Science, Japan Advanced Institute of Science and Technology

• NAKAMORI Yoshiteru

  School of Knowledge Science, Japan Advanced Institute of Science and Technology

• TAMURA Hiroyuki

  Department of Systems and Human Science, Graduate School of Engineering Science, Osaka University

Bibliographic Information

Other Title

• 適応型ファジィ回帰におけるパラメータの設定法
• テキオウガタ ファジィ カイキ ニ オケル パラメータ ノ セッテイホウ

Abstract

There are two types of design parameters in the adaptive fuzzy regression, which influences the result of clustering and regression. These parameters change the shapes of clusters adaptively by creating a balance between the regression residuals and the volumes of clusters. This paper suggests, in the context of fuzzy modeling, how to determine these parameters in order to obtain better regression models and fuzzy clusters simultaneously.

Journal

• Journal of Japan Society for Fuzzy Theory and Systems

  Journal of Japan Society for Fuzzy Theory and Systems 10 (2), 330-337, 1998

  Japan Society for Fuzzy Theory and Intelligent Informatics

Details

• CRID: 1390282679313604992
• NII Article ID: 110002939245
• NII Book ID: AN10231506
• DOI: 10.3156/jfuzzy.10.2_150
• ISSN: 24329932
• ISSN: 0915647X
• NDL BIB ID: 4458242
• Web Site: http://hdl.handle.net/10119/7963
• Web Site: http://id.ndl.go.jp/bib/4458242
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I4458242
• Web Site: https://www.jstage.jst.go.jp/article/jfuzzy/10/2/10_KJ00002086692/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • IRDB
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed