Building a Type-2 Fuzzy Qualitative Regression Model
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 regressi...
Saved in:
| Published in | Journal of advanced computational intelligence and intelligent informatics Vol. 16; no. 4; pp. 527 - 532 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
20.06.2012
|
| Online Access | Get full text |
Cover
Loading…
| Summary: | 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. |
|---|---|
| ISSN: | 1343-0130 1883-8014 |
| DOI: | 10.20965/jaciii.2012.p0527 |