ArticleOpen Access

SIMULATION OF FUZZY NEURAL NETWORK ALGORITHM IN DYNAMIC NONLINEAR SYSTEM

College of Big Data and Intelligent Engineering, Yangtze Normal University, Chongqing, P. R. China

Corresponding author.

Information Technology Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

E-mail Address: malasafi@kau.edu.sa

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, and

KE SONG

College of Mathematics and Information Engineering, Chongqing University of Education, Chongqing, P. R. China

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https://doi.org/10.1142/S0218348X22401065Cited by:5 (Source: Crossref)

This article is part of the issue:

Special Issue on Dynamical Systems and Their Applications to Engineering, Economy and Health Sciences
Guest Editors: Juan L. G. Guirao, Elbaz I. Abouelmagd and Bruce A. Wade

Abstract

The identification of nonlinear system is studied to establish an accurate model of coordination system. The original dynamic fuzzy neural network (DFNN) is first used to identify the nonlinear system for finding the existing problems. Aiming at the problems found, two improvements are made. For the problem of too many pre-set parameters in the original algorithm, the fuzzy completeness $ε -$ $𝜀 -$ is introduced to allocate the parameters, and the width of the membership function is modified. The simulation results reveal that the fuzzy neural network (FNN) model not improved produces seven fuzzy rules, and the root mean square error (RMSE) of training is 0.0261, while the improved FNN model produces six fuzzy rules, and the RMSE of training is 0.0161. The improved network has more advantages in performance. The model proposed provides some references for the application of FNN in dynamic nonlinear systems.

Keywords:

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Vol. 30, No. 02

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History

Received 8 December 2020

Accepted 14 July 2021

Published: February 3, 2022

Information

This is an Open Access article in the “Special Issue on Dynamical Systems and Their Applications to Engineering, Economy and Health Sciences”, edited by Juan L.G. Guirao (Technical University of Cartagena, Spain), Elbaz I. Abouelmagd (National Research Institute of Astronomy and Geophysics (NRIAG), Cairo, Egypt) & Bruce A. Wade (University of Louisiana at Lafayette, USA) published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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SIMULATION OF FUZZY NEURAL NETWORK ALGORITHM IN DYNAMIC NONLINEAR SYSTEM

Abstract

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