Estimation of Confidence Level ‘h’ in Fuzzy Linear Regression Analysis using Shape Preserving Operations

The aim of this discussion is to introduce a new fuzzy regression model, based on the distance between the outputs of the model in terms of its measurements along with the optimal confidence level ‘h’ using the shape preserving operations. Simple fuzzy regression models with fuzzy inputfuzzy outputs are also considered in which the coefficients of the models are themselves triangular fuzzy numbers. In the proposed method, the arithmetic operations are based on Tw norm, which preserves the shape during multiplication of two fuzzy numbers and it also satisfies the scale independent property. The numerical examples indicate that the proposed method has effective performance, especially when the data set includes some outliers. General Terms Fuzzy regression models, Shape preserving operations.