Meta-heuristic algorithms applied to the optimization of type-1 and type 2 TSK fuzzy logic systems for sea water level prediction

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.