Training ANFIS Using Genetic Algorithm for Dynamic Systems Identification

Bülent HAZNEDAR; Adem KALINLI

doi:10.18201/ijisae.266053

Authors

Bülent HAZNEDAR
Adem KALINLI

DOI:

https://doi.org/10.18201/ijisae.266053

Keywords:

Neuro-Fuzzy, ANFIS, Genetic Algorithm, System Identification

Abstract

In this study, the premise and consequent parameters of ANFIS are optimized using Genetic Algorithm (GA) based on a population algorithm. The proposed approach is applied to the nonlinear dynamic system identification problem. The simulation results of the method are compared with the Backpropagation (BP) algorithm and the results of other methods that are available in the literature. With this study it was observed that the optimisation of ANFIS parameters using GA is more successful than the other methods.

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