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 …

Purpose–The purpose of this paper is to critically review the latest approaches for capturing
and explaining heterogeneity in partial least squares (PLS) path modelling and to classify …

This paper presents a flexible algorithm based on artificial neural network (ANN) and fuzzy
regression (FR) to cope with optimum long-term oil price forecasting in noisy, uncertain, and …

This study presents an integrated fuzzy regression and time series framework to estimate
and predict electricity demand for seasonal and monthly changes in electricity consumption …

The success of new products depends greatly on customer satisfaction and meeting the
customer needs is vital for new product development. By incorporating customer needs in …

Trends in Fuzzy Statistics 1 Introduction Page 1 AUSTRIAN JOURNAL OF STATISTICS Volume
32 (2003), Number 3, 239-257 Trends in Fuzzy Statistics S. Mahmoud Taheri Isfahan University …

Most of previous studies on fuzzy regression analysis have a common characteristic of
increasing spreads for the estimated fuzzy responses as the independent variable increases …

Regression analysis is a statistical method employed to establish the relationship between"
independent variables" and" dependent variables." This widely utilized analysis technique is …

To estimate the parameters of fuzzy linear regression models with fuzzy output and crisp
inputs, we develop a mathematical programming model in this paper. The method is …

This study presents an integrated fuzzy system, data mining and time series framework to
estimate and predict electricity demand for seasonal and monthly changes in electricity …