Simple linear regression analysis for fuzzy input-output data and its application to psychological study

Kazuhisa Takemura*

*この研究の対応する著者

研究成果: Paper査読

抄録

A simple linear regression analysis using the least square method under some constraints, where both input data and output data are represented by triangular fuzzy numbers, was proposed and then compared to the possibilistic linear regression analysis proposed by Sakawa and Yano (1992) using fuzzy rating data in a psychological study. The major finding of the comparison were as follows: (1) Under the proposed analysis, the width between the upper and lower values of the predicted model was nearer to the width of the dependent variable than that of the possibilistic linear regression analysis, (2) As well, the representative value of the predicted value by the proposed analysis was also nearer to that of the dependent variable, compared with that of the possibilistic linear regression analysis.

本文言語English
ページ49-53
ページ数5
出版ステータスPublished - 1998 1 1
外部発表はい
イベントProceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, ICIPS'97. Part 1 (of 2) - Beijing, China
継続期間: 1997 10 281997 10 31

Other

OtherProceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, ICIPS'97. Part 1 (of 2)
CityBeijing, China
Period97/10/2897/10/31

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 工学(全般)

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