In this paper, we propose an iterative algorithm for multiple regression with fuzzy variables.While using the standard least-squares criterion as a performance index, we pose the regression problem as a gradient-descent optimisation. The separation of the evaluation of the gradient and the update of the regression variables makes it possible to avoid undue complication of analytical formulae fo...

in the course of the present study, the results of parametric approach are compared with those obtained through fuzzy approach using ahp as well as multivariate regression methods for comparisons and investigating the efficiency of the fuzzy method as applied in land suitability assessments. the correlation coefficients between land index and observed yield in the study area through fuzzy appro...

Abstract: Fuzzy regression models have been applied to several Operations Research applications viz., forecasting and prediction. Earlier works on fuzzy regression analysis obtain crisp regression coefficients for eliminating the problem of increasing spreads for the estimated fuzzy responses as the magnitude of the independent variable increases. But they cannot deal with the problem of non-un...

To calculate partial and total productivity of production factors in broiler farms in Yazd province, 72 manufacturing units were selected based on simple random sampling method and their information and statistics were collected for one production period in the second half of 2013. To measure productivity, the Cobb-Douglas production function was estimated using classic and fuzzy regression met...