constraints, etc. After having described the GME-fuzzy regression model, we consider an economic case study in which the features …

of remedial courses provided by an Italian university. We use a fuzzy regression discontinuity design to identify the …

In this study we suggest a Bayesian approach to fuzzy clustering analysis – the Bayesian fuzzy regression. Bayesian … Posterior Odds analysis is employed to select the correct number of clusters for the fuzzy regression analysis. In this study … Bayesian fuzzy regression are very encouraging. …

This paper introduces an integrated algorithm for forecasting electricity consumption (EL) based on fuzzy regression … variables for the fuzzy regression and time series models. Monthly EL in Iran is used to show the superiority of the algorithm …. Moreover, it is shown that the selected fuzzy regression model has better estimated values for total EL than time series. The …

The traditional fuzzy regression model involves two solving processes. First, the extension principle is used to derive … membership degree of at least h in the fuzzy regression interval. However, the membership function of extrapolated values is … proposed a simplified fuzzy regression equation based on Carlsson and Fullér’s possibilistic mean and variance method and used …