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Predicting water distribution pipe failures using machine learning and cross-infrastructure data
Daniel Kozelj, David Abert Fernández
Izvirni znanstveni članek
Oznake: water distribution systems;pipe failure prediction;machine learning;XGBoost;spatial analysis;condition assessment;
Water pipeline failures in urban networks are a significant source of non-revenue water, service disruptions, and high maintenance costs. This study develops a machine learning model to predict pipeline failure probabilities and inform risk-based maintenance strategies. Trained on real-world assets ...
Leto: 2025 Vir: Fakulteta za gradbeništvo in geodezijo (UL FGG)
AI-driven risk management for sustainable water distribution
David Abert Fernández, Hèctor Monclús, Bujar Fetai, Daniel Kozelj
Izvirni znanstveni članek
Oznake: water distribution networks;leakage failure;machine learning;resampling;
Aging water infrastructure and the resulting increase in pipe leaks pose significant operational and financial challenges for modern utilities, requiring more accurate tools for failure identification. This study presents a comprehensive benchmarking framework designed to predict pipe failure probab ...
Leto: 2026 Vir: Fakulteta za gradbeništvo in geodezijo (UL FGG)
Št. zadetkov: 2
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