Output details
15 - General Engineering
University of Huddersfield
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Article title
Multi-step ahead direct prediction for machine condition prognosis using regression trees and neuro-fuzzy systems
Type
D - Journal article
Title of journal
Expert Systems With Applications
Article number
-
Volume number
36
Issue number
5
First page of article
9378
ISSN of journal
0957-4174
Year of publication
2009
Number of additional authors
2
Additional information
This study presents a new approach based on artificial intelligence and time-series forecasting techniques to predict the degradation of machines and trends in fault propagation. In this work, long-term direct prediction method which is a challenging task in time-series prediction is considered. Additionally, a novel method for determining the number of essential observations and the number of steps which can be forecasted is proposed. As a result, the proposed approach allows tracking of changes in machine degradation and has potential for use as a machine prognosis tool.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-