Possibilistic linear regression analysis for fuzzy data

Hideo Tanaka, Isao Hayashi, Junzo Watada

研究成果: Article

266 引用 (Scopus)

抜粋

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.

元の言語English
ページ(範囲)389-396
ページ数8
ジャーナルEuropean Journal of Operational Research
40
発行部数3
DOI
出版物ステータスPublished - 1989 6 15
外部発表Yes

ASJC Scopus subject areas

  • Information Systems and Management
  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Modelling and Simulation
  • Transportation

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