JACIII Vol.16 No.4 pp. 527-532
doi: 10.20965/jaciii.2012.p0527


Building a Type-2 Fuzzy Qualitative Regression Model

Yicheng Wei and Junzo Watada

Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0135, Japan

December 29, 2011
April 15, 2012
June 20, 2012
type-2 fuzzy qualitative regression model, quantification, type-1 fuzzy set, type-2 fuzzy set, linear programming
Type-1 fuzzy regression model is constructed with type-1 fuzzy coefficients dealing with real value inputs and outputs. From the fuzzy set-theoretical point of view, uncertainty also exists when associated with qualitative data (membership degrees). This paper intends to build a qualitative regression model to measure uncertainty by applying the type-2 fuzzy set as the model’s coefficients. We are thus able to quantitatively describe the relationship between qualitative object variables and qualitative values of multivariate attributes (membership degree or type-1 fuzzy set), which are given by subjective recognition and judgment. We will build a basic qualitative model first and then improve it capable of ranging inputs. We will also give a heuristic solution in the end.
Cite this article as:
Y. Wei and J. Watada, “Building a Type-2 Fuzzy Qualitative Regression Model,” J. Adv. Comput. Intell. Intell. Inform., Vol.16 No.4, pp. 527-532, 2012.
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