A hybrid machine learning-based model for predicting failure of water mains under climatic variations: A Hong Kong case study-Reference-Cited by-同舟云学术

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A hybrid machine learning-based model for predicting failure of water mains under climatic variations: A Hong Kong case study

Published:2024-10 Issue: Volume:152 Page:105958
ISSN:0886-7798
Container-title:Tunnelling and Underground Space Technology
language:en
Short-container-title:Tunnelling and Underground Space Technology

Author:

Xing Jiduo^ORCID,Zayed Tarek,Dai Yanqing^ORCID,Shao Yuyang^ORCID,Almheiri Zainab^ORCID

Publisher

Elsevier BV

Reference55 articles.

1. An Approach to Predict the Failure of Water Mains Under Climatic Variations;Almheiri;Int. J. Geosynth. Ground Eng.,2020

2. Failure modeling of water distribution pipelines using meta-learning algorithms;Almheiri;Water Res.,2021

3. Predictive analytics for water main breaks using spatiotemporal data;Aslani;Urban Water J.,2021

4. Using generalized additive models to investigate the environmental effects on pipe failure in clean water networks;Barton;npj Clean Water,2020

5. An evolution of statistical pipe failure models for drinking water networks: a targeted review;Barton;Water Supply,2022

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