Improving pipe failure predictions: Factors affecting pipe failure in drinking water networks
To reduce leakage and improve service levels, water companies are increasingly using
statistical models of pipe failure using infrastructure, weather and environmental data …
statistical models of pipe failure using infrastructure, weather and environmental data …
Toward Sustainable Water Infrastructure: The State‐Of‐The‐Art for Modeling the Failure Probability of Water Pipes
Failures of water distribution networks (WDNs) are rising at an exponential rate,
necessitating immediate attention. An effective way to reduce the failure rate is to develop …
necessitating immediate attention. An effective way to reduce the failure rate is to develop …
Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors
Underground water pipes deteriorate under the influence of various physical, mechanical,
environmental, and social factors. Reliable pipe failure prediction is essential for a proactive …
environmental, and social factors. Reliable pipe failure prediction is essential for a proactive …
Pipe failure modelling for water distribution networks using boosted decision trees
Pipe failure modelling is an important tool for strategic rehabilitation planning of urban water
distribution infrastructure. Rehabilitation predictions are mostly based on existing network …
distribution infrastructure. Rehabilitation predictions are mostly based on existing network …
Uncertainty quantification of a deep learning model for failure rate prediction of water distribution networks
Predicting the time-dependent pipe failure rate of the water distribution networks (WDNs) is
important for planning its renewal budget but also challenging due to the complex factors …
important for planning its renewal budget but also challenging due to the complex factors …
Improving urban water security through pipe-break prediction models: Machine learning or survival analysis
North America's water distribution systems are aging and incurring increased pipe breaks.
These breaks pose a serious threat to urban drinking water security, leading to service …
These breaks pose a serious threat to urban drinking water security, leading to service …
Comparison of statistical and machine learning models for pipe failure modeling in water distribution networks
MM Giraldo-González, JP Rodríguez - Water, 2020 - mdpi.com
The application of statistical and Machine Learning models plays a critical role in planning
and decision support processes for efficient and reliable Water Distribution Network (WDN) …
and decision support processes for efficient and reliable Water Distribution Network (WDN) …
Integrated approach for pipe failure prediction and condition scoring in water infrastructure systems
Pipe failures in water distribution infrastructure have significant economic, environmental,
and public health impacts. To alleviate these impacts, pipe deterioration modeling has been …
and public health impacts. To alleviate these impacts, pipe deterioration modeling has been …
Systematic and scientometric analyses of predictors for modelling water pipes deterioration
The deterioration of water pipes causes significant socio-economic and environmental
burdens. Many predictors/factors are used to mitigate such problems by modelling the water …
burdens. Many predictors/factors are used to mitigate such problems by modelling the water …
Pipe breaks and estimating the impact of pressure control in water supply networks
The deterioration and fracture of water supply pipes present a major threat for the
continuous provision of drinking water. The hydraulic pressure in pipes is an influential …
continuous provision of drinking water. The hydraulic pressure in pipes is an influential …