Fuzzy robust regression analysis based on a hyperelliptic function

Junzo Watada*, Yoshiyuki Yabuuchi

*この研究の対応する著者

研究成果

12 被引用数 (Scopus)

抄録

Since a fuzzy linear regression model was proposed in 1987, its possibilistic model is employed to analyze data in various fields. From view points of fuzzy linear regression, data are interpreted to express the possibilities of a latent system. Therefore, when data have error or samples are irregular, the obtained regression model has unnaturally too wide possibility range. In this paper we propose a fuzzy robust linear regression model which is not influenced by data with error. Especially a hyperelliptic function is employed to select focal samples which may have large error or be irregular so that the number of combinatorial calculations can be reduced to a great extent. The model is built to minimize the total error between the model and the data. The robustness of the model is shown using numerical examples.

本文言語English
ホスト出版物のタイトルIEEE International Conference on Fuzzy Systems
編集者 Anon
Place of PublicationPiscataway, NJ, United States
出版社IEEE
ページ1841-1848
ページ数8
4
出版ステータスPublished - 1995
外部発表はい
イベントProceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) - Yokohama, Jpn
継続期間: 1995 3 201995 3 24

Other

OtherProceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5)
CityYokohama, Jpn
Period95/3/2095/3/24

ASJC Scopus subject areas

  • 化学的な安全衛生
  • ソフトウェア
  • 安全性、リスク、信頼性、品質管理

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