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.
DOI
https://doi.org/10.57709/1059367
Recommended Citation
Qiu, Yu, "Statistical Genetic Interval-Valued Type-2 Fuzzy System and its Application." Thesis, Georgia State University, 2006.
doi: https://doi.org/10.57709/1059367