Fuzzy Regression Models Using the Least-Squares Method based on the Concept of Distance: Simplified Approach

Regression models have been tremendously studying with so many applications in the presence of imprecise data. The regression coefficients are unknown i.e., they cannot be restricted. To the best of our knowledge, there is no approach except Chen and Hsueh approach (IEEE Transactions on Fuzzy Systems, vol. ۱۷, no. ۶, December ۲۰۰۹ pp.۱۲۵۹-۱۲۷۲) which can be used to find the regression coefficients of a fuzzy regression model without considering the non-negative restrictions on the regression coefficients. Chen and Hsueh have used some mathematical assumptions which lead to limitations in their approach. Furthermore, Chen and Hsueh approach is inefficient regarding to computational complexity. This paper proposed a simplified approach overcoming the limitations and computational complexity of Chen and Hsueh approach which can be considered by the researchers who would like to use Chen and Hsueh approach in real life applications.

کلیدواژه ها:

distance ، Fuzzy regression model ، fuzzy sets ، Least squares method