Statistical regression analysis is a powerful and reliable method to determine the impact of
one or several independent variable (s) on a dependent variable. It is the most widely used …

A fuzzy set extension known as the hesitant fuzzy set (HFS) has increased in popularity for
decision making in recent years, especially when experts have had trouble evaluating …

Fuzzy regression analysis was extensively used in previous studies to model the
relationships between dependent and independent variables in a fuzzy environment …

In time studies, estimation of the standard times with direct or indirect measurement methods
is particularly difficult in companies having complex production schedules or ones …

A bimodal distribution function with statistical parameters obtained using fuzzy regression is
presented for predicting random truckload patterns that include all load ranges including …

Purpose: In this study, factors affecting employment in non-life insurance companies were
examined. These factors are the financial variables of insurance companies, including …

Abstract change points. In addition, setting the change points to derive a piecewise fuzzy
regression model does not lead to a useful model, because we still do not know where to set …

Fuzzy regression models (FRMs) are used to describe the contribution of the corresponding
fuzzy explanatory variables in explaining the fuzzy response variable. The selection of …

Fuzzy regression has been applied to marketing, management, and sales forecasting for
many years. In this paper, two types of forecasting methods within the framework of fuzzy …

A method of variable selection for fuzzy regression has been proposed. Using the method,
the significance of fuzzy regression coefficients has been examined. The method presented …