A fuzzy regression model for predicting non-crisp variable

Huaitien Wang; Nang Fei Pan

doi:10.1109/FSKD.2008.296

A fuzzy regression model for predicting non-crisp variable

Huaitien Wang, Nang Fei Pan

Department of Civil Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Pages	104-106
Number of pages	3
DOIs	https://doi.org/10.1109/FSKD.2008.296
Publication status	Published - 2008 Dec 1
Event	5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008 - Jinan, Shandong, China Duration: 2008 Oct 18 → 2008 Oct 20

Publication series

Name	Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Volume	1

Other

Other	5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Country	China
City	Jinan, Shandong
Period	08-10-18 → 08-10-20

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Control and Systems Engineering

Access to Document

10.1109/FSKD.2008.296

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Cite this

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title = "A fuzzy regression model for predicting non-crisp variable",

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.",

author = "Huaitien Wang and Pan, {Nang Fei}",

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Wang, H & Pan, NF 2008, A fuzzy regression model for predicting non-crisp variable. in Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008., 4665948, Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008, vol. 1, pp. 104-106, 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008, Jinan, Shandong, China, 08-10-18. https://doi.org/10.1109/FSKD.2008.296

A fuzzy regression model for predicting non-crisp variable. / Wang, Huaitien; Pan, Nang Fei.

Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008. 2008. p. 104-106 4665948 (Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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