abstract background and purpose: since protein a is considered an important protein from medical, medicinal, genetic engineering, and biotechnology point of view, the present study attempted to investigate and determine to what extent protein a is produced through regression, in addition to the production conditions of the protein. thus, a figure was introduced as for the estimation of the amou...

Fuzzy linear regression is an interesting tool for handling uncertain data samples as an alternative to a probabilistic approach. This paper sets forth uses a linear regression model for fuzzy variables; the model is optimized through convex methods. A fuzzy linear programming model has been designed to solve the problem with nonlinear fuzzy data by combining the fuzzy arithmetic theory with co...

In a great deal of literature on fuzzy regression analysis, most of research has focused on some predefined parametric forms of fuzzy regression relationships, especially on the fuzzy linear regression models. In many practical situations, it may be unrealistic to predetermine a fuzzy parametric regression relationship. In this paper, a fuzzy nonparametric model with crisp input and LR fuzzy ou...

background: noise prediction is considered to be the best method for evaluating cost-preventative noise controls in industrial workrooms. one of the most important issues is the development of accurate models for analysis of the complex relationships among acoustic features affecting noise level in workrooms. in this study, advanced fuzzy approaches were employed to develop relatively accurate ...