Statistical Genetic Interval-Valued Fuzzy Systems with Prediction in Clinical Trials

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.