Advancements based on fuzzy regression model based on interval-valued fuzzy neural network and its applications to management

Regression is a fundamental component of data analysis and artificial intelligence that acts as a building block for this field. However, comprehensive lacks the development of regression models for interval-valued data that can be done as factors influencing these sets. In this paper, a fuzzy regression model based on an interval-valued fuzzy neural network and its applications to management is analyzed. We investigated some fuzzy regression models with type-۱ and type-۲ fuzzy regressions, namely IV-T۱FR and IV-T۲FR. The interval-valued fuzzy neural network (IVFNN) could be trained with clear and interval-valued fuzzy data. Here a neural network was considered as a method for analyzing and forecasting earned value schedule. This article introduces models based on interval fuzzy rule-based modeling (iFRB) and its application in management. Finally, we analyzed the affecting of this method and compared this method with existing methods.

Keywords:

Regression , interval-valued fuzzy , neural network