A Systematic Approach to Optimizing h Value for Fuzzy Linear Regression with Symmetric Triangular Fuzzy Numbers

A systematic approach is proposed to optimize h value for fuzzy linear regression (FLR) analysis using minimum fuzziness criteria with symmetric triangular fuzzy numbers (TFNs). Firstly, a new concept of credibility is defined to evaluate the performance of FLR models with different h values when a set of sample data pairs is given. Secondly, based on the defined concept of credibility, a programming model is formulated to optimize the value of h. Finally, both the numerical study and the real application show that the approach proposed in this paper is effective and efficient; that is, optimal value for h can be determined definitely with respect to a set of given sample data pairs.