Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Efficacy of Tree-Based Models for Pipe Failure Prediction and Condition Assessment: A Comprehensive Review
https://orcid.org/0000-0002-5275-3587
https://orcid.org/0000-0003-2814-9838
https://orcid.org/0000-0001-8376-4652
This paper provides a comprehensive review of tree-based models and their application in condition assessment and prediction of water, wastewater, and sewer pipe failures. Tree-based models have gained significant attention in recent years due to their effectiveness in capturing complex relationships between parameters of systems and their ability in handling large data sets. This study explores a range of tree-based models, including decision trees and ensemble trees utilizing bagging, boosting, and stacking strategies. The paper thoroughly examines the strengths and limitations of these models, specifically in the context of assessing the pipes’ condition and predicting their failures. In most cases, tree-based algorithms outperformed other prevalent models. Random forest was found to be the most frequently used approach in this field. Moreover, the models successfully predicted the failures when augmented with a richer failure data set. Finally, it was identified that existing evaluation metrics might not be necessarily suitable for assessing the prediction models in the water and sewer networks.
Efficacy of Tree-Based Models for Pipe Failure Prediction and Condition Assessment: A Comprehensive Review
https://orcid.org/0000-0002-5275-3587
https://orcid.org/0000-0003-2814-9838
https://orcid.org/0000-0001-8376-4652
This paper provides a comprehensive review of tree-based models and their application in condition assessment and prediction of water, wastewater, and sewer pipe failures. Tree-based models have gained significant attention in recent years due to their effectiveness in capturing complex relationships between parameters of systems and their ability in handling large data sets. This study explores a range of tree-based models, including decision trees and ensemble trees utilizing bagging, boosting, and stacking strategies. The paper thoroughly examines the strengths and limitations of these models, specifically in the context of assessing the pipes’ condition and predicting their failures. In most cases, tree-based algorithms outperformed other prevalent models. Random forest was found to be the most frequently used approach in this field. Moreover, the models successfully predicted the failures when augmented with a richer failure data set. Finally, it was identified that existing evaluation metrics might not be necessarily suitable for assessing the prediction models in the water and sewer networks.
Efficacy of Tree-Based Models for Pipe Failure Prediction and Condition Assessment: A Comprehensive Review
https://orcid.org/0000-0002-5275-3587
https://orcid.org/0000-0003-2814-9838
https://orcid.org/0000-0001-8376-4652
This paper provides a comprehensive review of tree-based models and their application in condition assessment and prediction of water, wastewater, and sewer pipe failures. Tree-based models have gained significant attention in recent years due to their effectiveness in capturing complex relationships between parameters of systems and their ability in handling large data sets. This study explores a range of tree-based models, including decision trees and ensemble trees utilizing bagging, boosting, and stacking strategies. The paper thoroughly examines the strengths and limitations of these models, specifically in the context of assessing the pipes’ condition and predicting their failures. In most cases, tree-based algorithms outperformed other prevalent models. Random forest was found to be the most frequently used approach in this field. Moreover, the models successfully predicted the failures when augmented with a richer failure data set. Finally, it was identified that existing evaluation metrics might not be necessarily suitable for assessing the prediction models in the water and sewer networks.
Efficacy of Tree-Based Models for Pipe Failure Prediction and Condition Assessment: A Comprehensive Review
J. Water Resour. Plann. Manage.
Latifi, Milad (Autor:in) / Beig Zali, Ramiz (Autor:in) / Javadi, Akbar A. (Autor:in) / Farmani, Raziyeh (Autor:in)
01.07.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| Taylor & Francis Verlag | 2012
| British Library Online Contents | 2012
| British Library Online Contents | 2014