IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Modeling of Uncertain Nonlinear System With Z-Numbers

Modeling of Uncertain Nonlinear System With Z-Numbers
View Sample PDF
Author(s): Raheleh Jafari (School of Design, University of Leeds, Leeds, UK), Sina Razvarz (Department of Automatic Control, Centre for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-IPN), Mexico City, Mexico), Alexander Gegov (School of Computing, University of Portsmouth, UK) and Satyam Paul (Department of Engineering Design and Mathematics, University of the West of England, Bristol, UK)
Copyright: 2021
Pages: 25
Source title: Encyclopedia of Information Science and Technology, Fifth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-7998-3479-3.ch022

Purchase

View Modeling of Uncertain Nonlinear System With Z-Numbers on the publisher's website for pricing and purchasing information.

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.

Related Content

Yair Wiseman. © 2021. 11 pages.
Mário Pereira Véstias. © 2021. 15 pages.
Mahfuzulhoq Chowdhury, Martin Maier. © 2021. 15 pages.
Gen'ichi Yasuda. © 2021. 12 pages.
Alba J. Jerónimo, María P. Barrera, Manuel F. Caro, Adán A. Gómez. © 2021. 19 pages.
Gregor Donaj, Mirjam Sepesy Maučec. © 2021. 14 pages.
Udit Singhania, B. K. Tripathy. © 2021. 11 pages.
Body Bottom