A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Integrating spatial clustering with predictive modeling of pipe failures in water distribution systems
Pipe failures in water distribution infrastructure (WDI) have significant economic, environmental and public health impacts. To alleviate these impacts, repair and replacement decisions need to be prioritized to effectively reduce failure rates. In this study, a computational framework is proposed for WDI asset management that couples spatial clustering analysis with predictive modeling of pipe failures. First, hotspot/coldspot clusters of statistically significant high/low failure rates are identified using local indicators of spatial association. Second, the predictive abilities of eight statistical learning techniques are systematically tested, and the best-performing method is implemented to forecast failure rates,(breaks/(km.year)) within different sectors of the WDI. Third, the framework is implemented to compare the impact of adopting proactive instead of reactive pipe replacement strategies. Applying the framework to a real-life, large-scale WDI revealed that spatial clustering of pipe failures improves the accuracy of the prediction models.
Integrating spatial clustering with predictive modeling of pipe failures in water distribution systems
Pipe failures in water distribution infrastructure (WDI) have significant economic, environmental and public health impacts. To alleviate these impacts, repair and replacement decisions need to be prioritized to effectively reduce failure rates. In this study, a computational framework is proposed for WDI asset management that couples spatial clustering analysis with predictive modeling of pipe failures. First, hotspot/coldspot clusters of statistically significant high/low failure rates are identified using local indicators of spatial association. Second, the predictive abilities of eight statistical learning techniques are systematically tested, and the best-performing method is implemented to forecast failure rates,(breaks/(km.year)) within different sectors of the WDI. Third, the framework is implemented to compare the impact of adopting proactive instead of reactive pipe replacement strategies. Applying the framework to a real-life, large-scale WDI revealed that spatial clustering of pipe failures improves the accuracy of the prediction models.
Integrating spatial clustering with predictive modeling of pipe failures in water distribution systems
Abokifa, Ahmed A. (author) / Sela, Lina (author)
Urban Water Journal ; 20 ; 465-476
2023-04-21
12 pages
Article (Journal)
Electronic Resource
Unknown
Application of genetic programming to modeling pipe failures in water distribution systems
| British Library Online Contents | 2011
Water distribution pipe replacement optimization based on spatial clustering
| DOAJ | 2023
Effects of pipe failures on water distribution networks
| British Library Conference Proceedings | 1995
| Wiley | 1925