Title :
Meta-heuristic algorithms applied to the optimization of type-1 and type 2 TSK fuzzy logic systems for sea water level prediction
Author :
Nguyen Cong Long ; Meesad, Phayung
Author_Institution :
Fac. of Inf. Technol., King Mongkut´s Univ. of Technol. North Bangkok, Bangkok, Thailand
Abstract :
This paper describes an approach using Firefly Algorithm, Particle Swarm Optimization and Genetic Algorithm to optimize the parameters of Takagi-Sugeno-Kang (TSK) fuzzy logic system (both type-1 and type-2) in order to find the optimal fuzzy logic system for sea water level prediction. The obtained results of the simulations performed are compared among these optimization algorithms in order to find which one is the best optimization algorithm for sea water level prediction.
Keywords :
fuzzy logic; fuzzy set theory; fuzzy systems; genetic algorithms; geophysics computing; particle swarm optimisation; sea level; seawater; Takagi-Sugeno-Kang fuzzy logic system; firefly algorithm; genetic algorithm; metaheuristic algorithms; optimal fuzzy logic system; optimization algorithm; parameter optimization; particle swarm optimization; sea water level prediction; type 2 TSK fuzzy logic system optimization; type-1 TSK fuzzy logic system; Artificial neural networks; Fuzzy logic; Genetic algorithms; Optimization; Particle swarm optimization; Prediction algorithms; Sociology; Firefly Algorithm; Genetic Algorithm; Interval Type-2 TSK Fuzzy Logic System; Particle Swarm Optimization; Sea Water Level Prediction; Type-1 TSK Fuzzy Logic System;
Conference_Titel :
Computational Intelligence & Applications (IWCIA), 2013 IEEE Sixth International Workshop on
Conference_Location :
Hiroshima
Print_ISBN :
978-1-4673-5725-8
DOI :
10.1109/IWCIA.2013.6624787
