Fuzzy data analysis by possibilistic linear models
Fuzzy Sets and Systems - Fuzzy Numbers
Information Sciences: an International Journal
Possibilistic linear systems and their application to the linear regression model
Fuzzy Sets and Systems
Evaluation of fuzzy linear regression models
Fuzzy Sets and Systems
Multiobjective fuzzy linear regression analysis for fuzzy input-output data
Fuzzy Sets and Systems
Fuzzy linear regression with fuzzy intervals
Fuzzy Sets and Systems
Properties of certain fuzzy linear regression methods
Fuzzy Sets and Systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A generalized fuzzy weighted least-squares regression
Fuzzy Sets and Systems
Fuzzy Sets and Systems
On the variance of fuzzy random variables
Fuzzy Sets and Systems
Information Sciences: an International Journal
Evaluation of fuzzy linear regression models by comparing membership functions
Fuzzy Sets and Systems
A linear regression model using triangular fuzzy number coefficients
Fuzzy Sets and Systems
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Fuzzy Multiple Attribute Decision Making: Methods and Applications
A fuzzy linear regression model with better explanatory power
Fuzzy Sets and Systems - Information processing
A new approach to fuzzy regression models with application to business cycle analysis
Fuzzy Sets and Systems
Multiple regression with fuzzy data
Fuzzy Sets and Systems
A simple approach to ranking a group of aggregated fuzzy utilities
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interval regression analysis by quadratic programming approach
IEEE Transactions on Fuzzy Systems
Interval regression analysis using quadratic loss support vector machine
IEEE Transactions on Fuzzy Systems
Fuzzy nonlinear regression with fuzzified radial basis function network
IEEE Transactions on Fuzzy Systems
Fuzzy Regression Analysis by Support Vector Learning Approach
IEEE Transactions on Fuzzy Systems
The Hybrid Fuzzy Least-Squares Regression Approach to Modeling Manufacturing Processes
IEEE Transactions on Fuzzy Systems
An affine fuzzy model with local and global interpretations
Applied Soft Computing
Fuzzy least-absolutes regression using shape preserving operations
Information Sciences: an International Journal
A two-stage approach for formulating fuzzy regression models
Knowledge-Based Systems
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Fuzzy regression models are developed to construct the relationship between explanatory variables and responses in a fuzzy environment. In order to increase the explanatory performance of the model, the least-squares method is applied to determine the numeric coefficients based on the concept of distance. Unlike most existing approaches, the numeric coefficients in the proposed model can have negative values. The proposed model minimizes total estimation error in terms of the sum of the average squared distance between the observed and estimated responses based on a few α-cuts. The proposed approach is not limited to triangular fuzzy numbers; it can be used to carry out a large number of fuzzy observations efficiently because the model is based on traditional statistical methods. Comparisons with existing methods show that based on the total estimation error using the mean squared error and Kim and Bishu's criterion, the explanatory performance of the proposed model is satisfactory.