Author

Yu QiuFollow

Date of Award

6-12-2006

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Dr. Yanqing Zhang - Chair

Second Advisor

Dr. Raj Sunderraman

Third Advisor

Dr. Ying Zhu

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. In order to make the type-2 fuzzy logic system reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and a new probability type reduced reasoning method for the interval-valued fuzzy logic system are proposed in this thesis. In order to optimize this particle system’s performance, we adopt genetic algorithm (GA) to adjust parameters. The applications for the new system are performed and results have shown that the developed method is more accurate and robust to design a reliable fuzzy logic system than type-1 method and the computation of our proposed method is more efficient.

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