Possibilistic linear regression analysis for fuzzy data

Hideo Tanaka*, Isao Hayashi, Junzo Watada

*この研究の対応する著者

研究成果: Article査読

291 被引用数 (Scopus)

抄録

Fuzzy data given by expert knowledge can be regarded as a possibility distribution by which possibilistic linear systems are defined. Recently, it has become important to deal with fuzzy data in connection with expert knowledge. Three formulations of possibilistic linear regression analysis are proposed here to deal with fuzzy data. Since our formulations can be reduced to linear programming problems, the merit of our formulations is to be able to obtain easily fuzzy parameters in possibilistic linear models and to add other constraint conditions which might be obtained from expert knowledge of fuzzy parameters. This approach can be regarded as a fuzzy interval analysis in a fuzzy environment.

本文言語English
ページ(範囲)389-396
ページ数8
ジャーナルEuropean Journal of Operational Research
40
3
DOI
出版ステータスPublished - 1989 6 15
外部発表はい

ASJC Scopus subject areas

  • 情報システムおよび情報管理
  • 経営科学およびオペレーションズ リサーチ
  • 統計学、確率および不確実性
  • 応用数学
  • モデリングとシミュレーション
  • 輸送

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