Type of Document Master's Thesis Author Qiu, Yu Author's Email Address yuq0916@hotmail.com URN etd-04102006-162051 Title Statistical Genetic Interval-Valued Type-2 Fuzzy System and its Application Degree Master of Science Department Computer Science Advisory Committee
Advisor Name Title Dr. Yanqing Zhang Committee Chair Dr. Raj Sunderraman Committee Member Dr. Ying Zhu Committee Member Keywords
- statistical interval-valued fuzzy reasoning
- type-2 fuzzy logic
- Interval-valued fuzzy logic
- fuzzy control
- genetic algorithm
Date of Defense 2006-04-05 Availability unrestricted 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.Files
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