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Fuzzy Robust Regression Model by Possibility Maximization
Author(s) -
Yoshiyuki Yabuuchi,
Junzo Watada
Publication year - 2011
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2011.p0479
Subject(s) - computer science , fuzzy logic , artificial intelligence , regression analysis , regression , data mining , machine learning , robust regression , fuzzy clustering , mathematics , statistics
Since management and economic systems are complex, it is hard to handle data obtained in management and economic areas. Hitherto, in the fields, much research has focused on the structure and analysis of such data. H. Tanaka et al. proposed a fuzzy regression model to illustrate the potential possibilities inherent in the target system. J. C. Bezdek proposed a switching regression model based on a fuzzy clustering model to separate mixed samples coming from plural latent systems and apply regression models to the groups of samples coming from each system. It is hard to illustrate a rough and moderate possibility of the target system. In this paper, to deal with the possibility of a social system, we propose a new fuzzy robust regression model.

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