Fuzzy regression analysis using fuzzy linear models with symmetric triangular fuzzy number coefficient has been introduced by Tanaka et al. The goal of this regression is to find the coefficient of a proposed model for all given input-output data sets. In this paper, we propose a new 1716 E. Pasha et al method for computation of fuzzy regression. The method is constructed on the basis of minimi...

The grade of membership (GoM) model uses fuzzy sets as memberships of each individual to extreme profiles (or classes) on the likelihood function of multivariate multinomial distributions. The GoM clustering algorithm derived from the GoM model is used in cluster analysis for categorical data, but it is iterated with complicated calculations. In this paper we create another approach, termed a f...

This paper transforms fuzzy number into clear number using the centroid method, thus we can research the traditional linear regression model which is transformed from the fuzzy linear regression model. The model’s input and output are fuzzy numbers, and the regression coefficients are clear numbers. This paper considers the parameter estimation and impact analysis based on data deletion. Throug...

Fuzzy linear regression analysis with symmetric triangular fuzzy number coefficient has been introduced by Tanaka et al. In this work we propose to approximate the fuzzy nonlinear regression using Artificial Neural Networks. The working of the proposed method is illustrated by the case study with the data for temperature and evaporation for the IARI New Delhi division. MSC: 62J86

Social judgment data was analyzed using fuzzy least squares regression analysis based on the extension principle. The proposed analysis is new fuzzy least squares regression analysis in which input data, output data, and coefficients are represented by L-R fuzzy numbers. To evaluate data fitness, we propose a fuzzy version of a squared multiple correlation (R) and conducted an experiment to det...

We introduce a new fuzzy linear regression method. The method is capable of approximating relationships between an independent and dependent variable. variables are expected to be real value triangular numbers, respectively. demonstrate on twenty datasets that the reliable, it less sensitive outliers, compare with possibilistic-based methods. Unlike other commonly used methods, presented simple...