DocumentCode
2385981
Title
Statistical Genetic Interval-Valued Fuzzy Systems with Prediction in Clinical Trials
Author
Qiu, Yu ; Zhang, Yan-Qing ; Zhao, Yichuan
Author_Institution
Georgia State Univ., Atlanta
fYear
2007
fDate
2-4 Nov. 2007
Firstpage
129
Lastpage
129
Abstract
In recent years, statistical tools and computational intelligence methods have played important roles in many areas. After statistically optimizing interval-valued fuzzy membership functions in the type-2 fuzzy logic system (FLS), we continue to apply genetic algorithms (GA) to optimize them. The proposed method is used to predict survival times for patients in clinical trials. The results show that the new GA-based method is more accurate than traditional type-1 and type-2 methods.
Keywords
fuzzy logic; fuzzy reasoning; fuzzy set theory; genetic algorithms; statistical analysis; clinical trials; computational intelligence methods; genetic algorithms; statistical genetic interval-valued fuzzy systems; statistical tools; type-2 fuzzy logic system; Clinical trials; Computational intelligence; Fuzzy logic; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Genetic algorithms; Least squares methods; Probability; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3032-1
Type
conf
DOI
10.1109/GrC.2007.89
Filename
4403081
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