An optimal design for type–2 fuzzy logic system using hybrid of chaos firefly algorithm and genetic algorithm and its application to sea level prediction
Affiliations: Faculty of Information Technology, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand
Note: [] Corresponding author. Nguyen Cong Long, Faculty of Information Technology, King Mongkut's University of Technology North Bangkok, 1518 Pracharat 1 Road, Wongsawang, Bangsue, Bangkok, Thailand. Tel.: +66 91 989 0954; E-mails: [email protected] (Nguyen Cong Long); [email protected] (Phayung Meesad).
Abstract: This paper proposes an optimal design for interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system. In this method, the fuzzy c-means clustering algorithm is used to determine structure of fuzzy rule as well as number of rules. A hybrid between chaos firefly algorithm and genetic algorithms (CFGA) is developed, which is used to find the desirable parameters of membership functions and consequents parameters of the fuzzy logic system. The obtained optimal fuzzy logic system is used to predict sea water level in short-term and long-term horizontal. To demonstrate the superiority of the hybrid algorithm in design the fuzzy logic system, comparison between CFGA with genetic algorithms and firefly algorithm applied to optimize the fuzzy logic system for sea water level prediction is investigated. Results illustrate CFGA approach to design fuzzy logic system to be highly comparative, outperforming both genetic algorithms and firefly algorithm.
