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

fYear

2013

fDate

13-13 July 2013

Firstpage

69

Lastpage

74

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence & Applications (IWCIA), 2013 IEEE Sixth International Workshop on

Conference_Location

Hiroshima

ISSN

1883-3977

Print_ISBN

978-1-4673-5725-8

Type

conf

DOI

10.1109/IWCIA.2013.6624787

Filename

6624787