DocumentCode :
477663
Title :
A Fuzzy Regression Model for Predicting Non-crisp Variable
Author :
Wang, Huaitien ; Pan, Nang-Fei
Volume :
1
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
104
Lastpage :
106
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 matrix-driven 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.
Keywords :
fuzzy set theory; matrix algebra; regression analysis; engineering prediction; matrix-driven multiple fuzzy linear regression model; noncrisp variable prediction; ordinary regression analysis; Civil engineering; Costs; Fuzzy systems; Knowledge engineering; Linear regression; Logistics; Matrices; Power system modeling; Predictive models; Regression analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Shandong
Print_ISBN :
978-0-7695-3305-6
Type :
conf
DOI :
10.1109/FSKD.2008.296
Filename :
4665948
Link To Document :
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