HYBRID FEATURE SELECTION AND SUPPORT VECTOR MACHINE FRAMEWORK FOR PREDICTING MAINTENANCE FAILURES

HYBRID FEATURE SELECTION AND SUPPORT VECTOR MACHINE FRAMEWORK FOR PREDICTING MAINTENANCE FAILURES

The main aim of predictive maintenance is to minimize downtime, failure risks and maintenance costs in manufacturing systems. Over the past few years, machine learning methods gained ground with diverse and successful applications in the area of predictive maintenance. This study shows that performi...

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Bibliographic Details
Main Authors: Mouna TARIK, Ayoub MNIAI, Khalid JEBARI
Format: Article
Language:English
Published: Polish Association for Knowledge Promotion 2023-06-01
Series:Applied Computer Science
Subjects:
predictive maintenance
machine learning
features selection
smote-tomek
support vector machine
Online Access:http://www.acs.pollub.pl/index.php?option=com_content&view=article&id=569:hybrid-feature-selection-and-support-vector-machine-framework-for-predicting-maintenance-failures&catid=97:vol-19-no-22023&Itemid=171

Internet

http://www.acs.pollub.pl/index.php?option=com_content&view=article&id=569:hybrid-feature-selection-and-support-vector-machine-framework-for-predicting-maintenance-failures&catid=97:vol-19-no-22023&Itemid=171

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