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Prediction of pipe failures in water supply networks using logistic regression and support vector classification

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  • Robles-Velasco, Alicia
  • Cortés, Pablo
  • Muñuzuri, Jesús
  • Onieva, Luis

Abstract

Companies in charge of water supply networks are making a huge effort to optimally plan the annual replacements of pipes. This would save costs, enable a higher quality of service and a sustainable management of infrastructure.

Suggested Citation

  • Robles-Velasco, Alicia & Cortés, Pablo & Muñuzuri, Jesús & Onieva, Luis, 2020. "Prediction of pipe failures in water supply networks using logistic regression and support vector classification," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:reensy:v:196:y:2020:i:c:s095183201930417x
    DOI: 10.1016/j.ress.2019.106754
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    References listed on IDEAS

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    1. Kabir, Golam & Tesfamariam, Solomon & Sadiq, Rehan, 2015. "Predicting water main failures using Bayesian model averaging and survival modelling approach," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 498-514.
    2. Francis, Royce A. & Guikema, Seth D. & Henneman, Lucas, 2014. "Bayesian Belief Networks for predicting drinking water distribution system pipe breaks," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 1-11.
    3. Kabir, Golam & Tesfamariam, Solomon & Francisque, Alex & Sadiq, Rehan, 2015. "Evaluating risk of water mains failure using a Bayesian belief network model," European Journal of Operational Research, Elsevier, vol. 240(1), pages 220-234.
    4. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
    5. Xu, Qiang & Chen, Qiuwen & Li, Weifeng & Ma, Jinfeng, 2011. "Pipe break prediction based on evolutionary data-driven methods with brief recorded data," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 942-948.
    6. Ahmed M. A. Sattar & B. Gharabaghi & Edward A. McBean, 2016. "Prediction of Timing of Watermain Failure Using Gene Expression Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1635-1651, March.
    7. Wang, Fei & Zheng, Xia-zhong & Li, Nan & Shen, Xuesong, 2019. "Systemic vulnerability assessment of urban water distribution networks considering failure scenario uncertainty," International Journal of Critical Infrastructure Protection, Elsevier, vol. 26(C).
    8. Ahmed Sattar & B. Gharabaghi & Edward McBean, 2016. "Prediction of Timing of Watermain Failure Using Gene Expression Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1635-1651, March.
    9. Debón, A. & Carrión, A. & Cabrera, E. & Solano, H., 2010. "Comparing risk of failure models in water supply networks using ROC curves," Reliability Engineering and System Safety, Elsevier, vol. 95(1), pages 43-48.
    10. Symeon Christodoulou & Alexandra Deligianni, 2010. "A Neurofuzzy Decision Framework for the Management of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(1), pages 139-156, January.
    11. Yamijala, Shridhar & Guikema, Seth D. & Brumbelow, Kelly, 2009. "Statistical models for the analysis of water distribution system pipe break data," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 282-293.
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    Cited by:

    1. Katarzyna Pietrucha-Urbanik & Barbara Tchórzewska-Cieślak & Mohamed Eid, 2021. "A Case Study in View of Developing Predictive Models for Water Supply System Management," Energies, MDPI, vol. 14(11), pages 1-25, June.
    2. Liu, Jie & Xu, Yubo & Wang, Lisong, 2022. "Fault information mining with causal network for railway transportation system," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    3. Mehryar, Mehdi & Hafezalkotob, Ashkan & Azizi, Amir & Sobhani, Farzad Movahedi, 2023. "Dynamic zoning of the network using cooperative transmission and maintenance planning: A solution for sustainability of water distribution networks," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Salehi, Sattar & Robles-Velasco, Alicia & Seyedzadeh, Ali & Ghazali, Aliakbar & Davoudiseresht, Mohsen, 2022. "A hybrid knowledge-based method for pipe renewal planning in Water Distribution Systems with limited data: Application to Iran," Utilities Policy, Elsevier, vol. 78(C).
    5. Wu, Jason & Baker, Jack W., 2020. "Statistical learning techniques for the estimation of lifeline network performance and retrofit selection," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    6. Fan, Xudong & Wang, Xiaowei & Zhang, Xijin & ASCE Xiong (Bill) Yu, P.E.F., 2022. "Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    7. Ramos-Salgado, Cristóbal & Muñuzuri, Jesús & Aparicio-Ruiz, Pablo & Onieva, Luis, 2021. "A decision support system to design water supply and sewer pipes replacement intervention programs," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    8. Jara-Arriagada, Carlos & Stoianov, Ivan, 2021. "Pipe breaks and estimating the impact of pressure control in water supply networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    9. Katarzyna Pietrucha-Urbanik & Barbara Tchórzewska-Cieślak & Mohamed Eid, 2020. "Water Network-Failure Data Assessment," Energies, MDPI, vol. 13(11), pages 1-14, June.
    10. Yihong Guan & Mou Lv & Shen Dong, 2023. "Pressure-driven Background Leakage Models and their Application for Leak Localization Using a Multi-population Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 359-373, January.
    11. Rifaai, Talha M. & Abokifa, Ahmed A. & Sela, Lina, 2022. "Integrated approach for pipe failure prediction and condition scoring in water infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    12. Wei Liu & Binhao Wang & Zhaoyang Song, 2022. "Failure Prediction of Municipal Water Pipes Using Machine Learning Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1271-1285, March.
    13. Ramos-Salgado, Cristóbal & Muñuzuri, Jesús & Aparicio-Ruiz, Pablo & Onieva, Luis, 2022. "A comprehensive framework to efficiently plan short and long-term investments in water supply and sewer networks," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    14. Alicia Robles-Velasco & Cristóbal Ramos-Salgado & Jesús Muñuzuri & Pablo Cortés, 2021. "Artificial Neural Networks to Forecast Failures in Water Supply Pipes," Sustainability, MDPI, vol. 13(15), pages 1-10, July.
    15. Zio, Enrico, 2022. "Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    16. Yaser Amiri-Ardakani & Mohammad Najafzadeh, 2021. "Pipe Break Rate Assessment While Considering Physical and Operational Factors: A Methodology based on Global Positioning System and Data-Driven Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3703-3720, September.
    17. Daulat, Shamsuddin & Rokstad, Marius Møller & Bruaset, Stian & Langeveld, Jeroen & Tscheikner-Gratl, Franz, 2024. "Evaluating the generalizability and transferability of water distribution deterioration models," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    18. Fan, Xudong & Zhang, Xijin & Yu, Xiong Bill, 2023. "Uncertainty quantification of a deep learning model for failure rate prediction of water distribution networks," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    19. Ling, Chunyan & Lu, Zhenzhou & Zhang, Xiaobo, 2020. "An efficient method based on AK-MCS for estimating failure probability function," Reliability Engineering and System Safety, Elsevier, vol. 201(C).

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