Explainable ensemble models for predicting wall thickness loss of water pipes

Explainable ensemble models for predicting wall thickness loss of water pipes

Water Distribution Networks (WDNs) are susceptible to pipe failures with significant consequences. Predicting wall-thickness loss in pipes is vital for proactive maintenance and asset management. This study develops optimized, explainable machine learning models for this purpose. Data from four WDNs...

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Bibliographic Details
Main Authors: Ridwan Taiwo, Abdul-Mugis Yussif, Mohamed El Amine Ben Seghier, Tarek Zayed
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Ain Shams Engineering Journal
Subjects:
Water pipelines
Wall thickness
Machine learning
Ensemble learning
SHAP
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447924000054

Internet

http://www.sciencedirect.com/science/article/pii/S2090447924000054

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