Training ANFIS structure with modified PSO algorithm

Author

Ghomsheh, V. Seydi ; Shoorehdeli, M. Aliyari ; Teshnehlab, M.

Author_Institution

Islamic Azad Univ., Kermanshah

fYear

2007

fDate

27-29 June 2007

Firstpage

1

Lastpage

6

Abstract

This paper introduces a new approach for training the adaptive network based fuzzy inference system (ANFIS). The previous works emphasized on gradient base method or least square (LS) based method. In this study we apply one of the swarm intelligent branches, named particle swarm optimization (PSO) with some modification in it to the training of all parameters of ANFIS structure. These modifications are inspired by natural evolutions. Finally the method is applied to the identification of nonlinear dynamical system and is compared with basic PSO and showed quite satisfactory results.

Keywords

adaptive systems; fuzzy reasoning; learning (artificial intelligence); nonlinear dynamical systems; particle swarm optimisation; ANFIS structure; adaptive network based fuzzy inference system; modified PSO algorithm; nonlinear dynamical system identification; particle swarm optimization; Adaptive systems; Computer networks; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Intelligent structures; Intelligent systems; Neural networks; Nonlinear dynamical systems; Particle swarm optimization; ANFIS; Fuzzy Systems; Identification; Neuro-Fuzzy; Particle Swarm Optimization; Swarm Intelligent; TSK System;

fLanguage

English

Publisher

ieee

Conference_Titel

Control & Automation, 2007. MED '07. Mediterranean Conference on

Conference_Location

Athens

Print_ISBN

978-1-4244-1282-2

Electronic_ISBN

978-1-4244-1282-2

Type

conf

DOI

10.1109/MED.2007.4433927

Filename

4433927