Title
Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors
Abstract
•Studied the safety and reliability analysis of water supply network (WSN) in terms of pipe's break probability prediction.•Developed data fusion framework to integrate multi-sourced datasets, leading to the largest real-field dataset related to WSN.•Applied machine learning algorithms to analyze the aggregated dataset and their performance compared.•Analyzed the effects of engineering, geology, climate and socioeconomic factors on WSN service conditions.•Advanced WSN safety and management for water management agencies and stakeholders.
Year
DOI
Venue
2022
10.1016/j.ress.2021.108185
Reliability Engineering & System Safety
Keywords
DocType
Volume
Multi-source data aggregation,Machine learning,Water supply network,Pipe failure prediction
Journal
219
ISSN
Citations 
PageRank 
0951-8320
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Xudong Fan100.34
Xiao-Wei Wang259659.78
Xijin Zhang300.34
Xiong (Bill) Yu400.34