Title :
Identification of high-dimensional fuzzy classification systems based on Multi-objective genetic algorithm
Author :
Yong, Zhang ; Xiaobei, Wu ; Zhiliang, Xu ; Cheng, Huang
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing
Abstract :
A novel approach to construct accurate and interpretable high-dimensional fuzzy classification system is proposed in this paper. First, in order to relieve the problem of dimension disaster, a feature selection is accomplished by the Simba algorithm. Then a fuzzy clustering algorithm is using to identify an initial fuzzy system. Finally the structure and parameters of the fuzzy system are optimized by Multi-objective genetic algorithm. The proposed approach is applied to the Wisconsin Breast Cancer benchmark problem, and the results show its validity.
Keywords :
feature extraction; fuzzy systems; genetic algorithms; pattern classification; pattern clustering; Simba algorithm; Wisconsin Breast Cancer benchmark problem; dimension disaster; feature selection; fuzzy clustering algorithm; fuzzy system; high-dimensional fuzzy classification systems; multiobjective genetic algorithm; Automation; Breast cancer; Clustering algorithms; Control systems; Electronic mail; Fuzzy control; Fuzzy sets; Fuzzy systems; Genetic algorithms; Merging; Feature selection; Fuzzy classification systems; Fuzzy clustering; Genetic algorithm; Interpretability; Pareto optimal solution;
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
DOI :
10.1109/CHICC.2008.4605663
