Fuzzy robust regression analysis

Junzo Watada*, Yoshiyuki Yabuuchi

*この研究の対応する著者

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

Since a fuzzy linear regression model has been proposed in 1987, its possibilistic model is employed to analyze data. From view points of fuzzy linear regression, data are understood to express the possibilities of a latent system. When data have error or data are very irregular, the obtained regression model has unnaturally too wide possibility range. In this paper we propose a fuzzy robust linear regression which is not influenced by data with error. The model is built as rigid a model as possible to minimize the total error between the model and the data. The robustness of the proposed 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
Place of PublicationPiscataway, NJ, United States
出版社IEEE
ページ1370-1376
ページ数7
2
出版ステータスPublished - 1994
外部発表はい
イベントProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA
継続期間: 1994 6 261994 6 29

Other

OtherProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3)
CityOrlando, FL, USA
Period94/6/2694/6/29

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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