Polynomial regression interval-valued fuzzy systems

Authors:
Yu Qiu;Hong Yang;Yan-Qing Zhang;Yichuan Zhao
Affiliations:
Georgia State University, Department of Computer Science, 30302-3994, Atlanta, GA, USA;Georgia State University, Department of Computer Science, 30302-3994, Atlanta, GA, USA;Georgia State University, Department of Computer Science, 30302-3994, Atlanta, GA, USA;Georgia State University, Department of Mathematics and Statistics, 30303, Atlanta, GA, USA
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Year:
2007

Citing 0
Cited 3

Methods of critical value reduction for type-2 fuzzy variables and their applications

Journal of Computational and Applied Mathematics
Review: Industrial applications of type-2 fuzzy sets and systems: A concise review

Computers in Industry
An interval-valued fuzzy controller for complex dynamical systems with application to a 3-PSP parallel robot

Fuzzy Sets and Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system (FLS). In order to make the type-2 FLS reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and probability type reduce reasoning method for the interval-valued FLS are developed. We have implemented the proposed non-linear (polynomial regression) statistical interval-valued type-2 FLS to perform smart washing machine control. The results show that our quadratic statistical method is more robust to design a reliable type-2 FLS and also can be extend to polynomial model.