Using the fuzzy technique to identification stochastic linear dynamic systems

The issue of dealing with the diagnostic process of any dynamic system is of great importance. Diagnostic becomes more difficult and complex in the case of non-stationary systems. This research deals with two diagnosis methods of dynamic systems, namely classical and logic diagnosis. The two methods...

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Bibliographic Details
Published in:	Journal of statistics & management systems Vol. 24; no. 4; pp. 801 - 808
Main Authors:	Hayawi, Heyam A. A., Ibrahim, Najlaa Saad, Mohammed, Lamyaa Jasim
Format:	Journal Article
Language:	English
Published:	New Delhi Taylor & Francis 19-05-2021 Taru Publications
Subjects:	Diagnosis Diagnostic systems Dynamic systems Dynamical systems Fuzziness Fuzzy logic Membership functions Time series
Online Access:	Get full text
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Summary:	The issue of dealing with the diagnostic process of any dynamic system is of great importance. Diagnostic becomes more difficult and complex in the case of non-stationary systems. This research deals with two diagnosis methods of dynamic systems, namely classical and logic diagnosis. The two methods were applied on teal data previously treated by Box and Jenkins (1976).The comparison has been done depending on checking many statistical, and engineering conditions. The results of fuzzy techniques were better than the classical techniques.
ISSN:	0972-0510 2169-0014
DOI:	10.1080/09720510.2020.1859808