Employing machine learning in water infrastructure management: predicting pipeline failures for improved maintenance and sustainable operations
Abstract This study explores techniques for managing class imbalance in predictive modeling to forecast water pipe failures using XGBoost and logistic regression. Given the significant challenges posed by water pipeline failures—such as service disruptions, costly repairs, and environmental hazards—...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2024-11-01
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| Series: | Industrial Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44244-024-00022-w |
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