Modeling of uncertain nonlinear system with Z-numbers

Raheleh Jafari; Sina Razvarz; Alexander Gegov; Satyam Paul

doi:10.4018/978-1-7998-3479-3.ch022

Modeling of uncertain nonlinear system with Z-numbers

Raheleh Jafari
, Sina Razvarz
, Alexander Gegov
, Satyam Paul

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

In order to model the fuzzy nonlinear systems, fuzzy equations with Z-number coefficients are used in this chapter. The modeling of fuzzy nonlinear systems is to obtain the Z-number coefficients of fuzzy equations. In this work, the neural network approach is used for finding the coefficients of fuzzy equations. Some examples with applications in mechanics are given. The simulation results demonstrate that the proposed neural network is effective for obtaining the Z-number coefficients of fuzzy equations.

Original language	English
Title of host publication	Encyclopedia of Information Science and Technology, Fifth Edition
Editors	Mehdi Khosrow-Pour
Publisher	IGI Global
Chapter	22
Pages	290-314
Number of pages	25
Edition	5th
ISBN (Electronic)	9781799834809
ISBN (Print)	9781799834793
DOIs	https://doi.org/10.4018/978-1-7998-3479-3.ch022 https://doi.org/10.4018/978-1-7998-3479-3
Publication status	Published - 24 Jul 2020

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https://www.igi-global.com/gateway/chapter/260193

Cite this

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AB - In order to model the fuzzy nonlinear systems, fuzzy equations with Z-number coefficients are used in this chapter. The modeling of fuzzy nonlinear systems is to obtain the Z-number coefficients of fuzzy equations. In this work, the neural network approach is used for finding the coefficients of fuzzy equations. Some examples with applications in mechanics are given. The simulation results demonstrate that the proposed neural network is effective for obtaining the Z-number coefficients of fuzzy equations.

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Modeling of uncertain nonlinear system with Z-numbers

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