Paper Info
Title
Building A Type-2 Fuzzy Qualitative Regression Model
Abstract
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.
Year
DOI
Venue
2012
10.20965/jaciii.2012.p0527
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS
Keywords
DocType
Volume
type-2 fuzzy qualitative regression model, quantification, type-1 fuzzy set, type-2 fuzzy set, linear programming
Journal
16
Issue
ISSN
Citations 
4
1343-0130
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Yicheng Wei131.42
Junzo Watada241184.53