A fuzzy regression model for predicting non-crisp variable

Huaitien Wang, Nang Fei Pan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Ordinary regression analysis is one of the most powerful approaches for the applications in engineering predictions. However, ordinary regression techniques are incapable of analyzing non-crisp or fuzzy observed data. This paper presents a matrixdriven multiple fuzzy linear regression model. The proposed model can deal with a mixture of fuzzy data and crisp data. An illustrative example is presented to illustrate the use of the proposed model. The result shows the capability of the proposed model.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Pages104-106
Number of pages3
DOIs
Publication statusPublished - 2008 Dec 1
Event5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008 - Jinan, Shandong, China
Duration: 2008 Oct 182008 Oct 20

Publication series

NameProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Volume1

Other

Other5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
CountryChina
CityJinan, Shandong
Period08-10-1808-10-20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

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