Author(s)

Jun Deng, Qiujun Lu

University of Shanghai for Science and Technology, Shanghai, China.

Some existed fuzzy regression methods have some special requirements for the object of study, such as assuming the observed values as symmetric triangular fuzzy numbers or imposing a non-negative constraint of regression parameters. In this paper, we propose a left-right fuzzy regression method, which is applicable to various forms of observed values. We present a fuzzy distance and partial order between two left-right (LR) fuzzy numbers and we let the mean fuzzy distance between the observed and estimated values as the mean fuzzy error, then make the mean fuzzy error minimum to get the regression parameter. We adopt two criteria involving mean fuzzy error (comparative mean fuzzy error based on partial order) and SSE to compare the performance of our proposed method with other methods. Finally four different types of numerical examples are given to illustrate that our proposed method has feasibility and wide applicability.

LR Fuzzy Number, LR Fuzzy Distance Measure, Mean Fuzzy Error, Fuzzy Regression

Deng, J. and Lu, Q. (2018) Fuzzy Regression Model Based on Fuzzy Distance Measure. Journal of Data Analysis and Information Processing, 6, 126-140. doi: 10.4236/jdaip.2018.63008.