Title :
Multi-objective fuzzy modeling using NSGA-II
Author :
Zong-Yi, Xing ; Yong, Zhang ; Yuan-long, Hou ; Guo-Qiang, Cai
Author_Institution :
Sch. of Mech. Eng., Nanjing Univ. of Sci. & Technol., Nanjing
Abstract :
An approach to construct multiple Pareto-optimal fuzzy systems based on NSGA-II is proposed in this paper. First, in order to obtain a good initial fuzzy system, a modified fuzzy clustering algorithm is used to identify the antecedents of fuzzy system, while the consequents are designed separately to reduce computational burden. Second, a Pareto multi-objective genetic algorithm based on NSGA-II and the interpretability-driven simplification techniques are used to evolve the initial fuzzy system iteratively with three objectives: the precision performance, the number of fuzzy rules and the number of fuzzy sets. Resultantly, multiple Pareto- optimal fuzzy systems are obtained. The proposed approach is applied to two benchmark problems, and the results show its validity.
Keywords :
Pareto optimisation; fuzzy set theory; genetic algorithms; NSGA-II; Pareto multi-objective genetic algorithm; fuzzy sets; interpretability-driven simplification techniques; modified fuzzy clustering algorithm; multi-objective fuzzy modeling; multiple Pareto-optimal fuzzy systems; Algorithm design and analysis; Clustering algorithms; Decision making; Evolutionary computation; Fuzzy sets; Fuzzy systems; Genetic algorithms; Mechanical engineering; Predictive models; Traffic control; Fuzzy modeling; NSGA-II; Pareto-optimal; fuzzy system; interpretability; multi-objective genetic algorithm;
Conference_Titel :
Cybernetics and Intelligent Systems, 2008 IEEE Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-1673-8
Electronic_ISBN :
978-1-4244-1674-5
DOI :
10.1109/ICCIS.2008.4670812
