SIMULATION OF FUZZY NEURAL NETWORK ALGORITHM IN DYNAMIC NONLINEAR SYSTEM

Jun Zeng, Madini O. Alassafi () and Ke Song
Additional contact information
Jun Zeng: College of Big Data and Intelligent Engineering, Yangtze Normal University, Chongqing, P. R. China
Madini O. Alassafi: ��Information Technology Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
Ke Song: ��College of Mathematics and Information Engineering, Chongqing University of Education, Chongqing, P. R. China

FRACTALS (fractals), 2022, vol. 30, issue 02, 1-11

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 𠜀− 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: Dynamic Fuzzy Neural Network; Nonlinear System; Non-Parametric Model; Elliptic Basis (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X22401065
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:30:y:2022:i:02:n:s0218348x22401065

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X22401065

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().