Possibilistic linear systems and their application to the linear regression model

H. Tanaka*, J. Watada

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

373 Citations (Scopus)

Abstract

It is the purpose of this paper to illustrate possibilistic linear systems based on possibility measure and to formulate a linear regression analysis by possibilistic linear models. Linear regression by a possibilistic model is called possibilistic linear regression. This is a new interpretation of fuzzy linear regression and also includes a new method by which interval analysis can be done in fuzzy numbers.

Original languageEnglish
Pages (from-to)275-289
Number of pages15
JournalFuzzy Sets and Systems
Volume27
Issue number3
DOIs
Publication statusPublished - 1988
Externally publishedYes

Keywords

  • Fuzzy system equations
  • Linear regression model
  • Possibilistic linear systems

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Statistics, Probability and Uncertainty
  • Electrical and Electronic Engineering
  • Statistics and Probability

Fingerprint

Dive into the research topics of 'Possibilistic linear systems and their application to the linear regression model'. Together they form a unique fingerprint.

Cite this