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Comparing risk of failure models in water supply networks using ROC curves

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  • Debón, A.
  • Carrión, A.
  • Cabrera, E.
  • Solano, H.

Abstract

The problem of predicting the failure of water mains has been considered from different perspectives and using several methodologies in engineering literature. Nowadays, it is important to be able to accurately calculate the failure probabilities of pipes over time, since water company profits and service quality for citizens depend on pipe survival; forecasting pipe failures could have important economic and social implications. Quantitative tools (such as managerial or statistical indicators and reliable databases) are required in order to assess the current and future state of networks. Companies managing these networks are trying to establish models for evaluating the risk of failure in order to develop a proactive approach to the renewal process, instead of using traditional reactive pipe substitution schemes.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:1:p:43-48
    DOI: 10.1016/j.ress.2009.07.004
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    References listed on IDEAS

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    1. 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. 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.
    3. Catherine Ragasa & Suzanne Thornsbury & Satish Joshi, 2017. "Dynamics of EU food safety certification: a survival analysis of firm decisions," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 5(1), pages 1-25, December.
    4. 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.
    5. Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2015. "Predictive inference for system reliability after common-cause component failures," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 27-33.
    6. 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).
    7. Zio, E. & Golea, L.R., 2012. "Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 67-74.
    8. 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).
    9. García-Mora, B. & Debón, A. & Santamaría, C. & Carrión, A., 2015. "Modelling the failure risk for water supply networks with interval-censored data," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 311-318.
    10. Xiao, Rui & Zayed, Tarek & Meguid, Mohamed A. & Sushama, Laxmi, 2024. "Improving failure modeling for gas transmission pipelines: A survival analysis and machine learning integrated approach," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    11. 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.
    12. Gema Sakti Raspati & Stian Bruaset & Camillo Bosco & Lars Mushom & Birgitte Johannessen & Rita Ugarelli, 2022. "A Risk-Based Approach in Rehabilitation of Water Distribution Networks," IJERPH, MDPI, vol. 19(3), pages 1-24, January.
    13. Kong Fah Tee & Lutfor Rahman Khan & Tahani Coolen-Maturi, 2015. "Application of receiver operating characteristic curve for pipeline reliability analysis," Journal of Risk and Reliability, , vol. 229(3), pages 181-192, June.
    14. Debón, A. & Carlos Garcia-Díaz, J., 2012. "Fault diagnosis and comparing risk for the steel coil manufacturing process using statistical models for binary data," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 102-114.
    15. Andrés Carrión & Hernando Solano & María Gamiz & Ana Debón, 2010. "Evaluation of the Reliability of a Water Supply Network from Right-Censored and Left-Truncated Break Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(12), pages 2917-2935, September.
    16. Kozłowski Edward & Kowalska Beata & Kowalski Dariusz & Mazurkiewicz Dariusz, 2019. "Survival Function in the Analysis of the Factors Influencing the Reliability of Water Wells Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4909-4921, November.
    17. Pradeep Amarasinghe & An Liu & Prasanna Egodawatta & Paul Barnes & James McGree & Ashantha Goonetilleke, 2017. "Modelling Resilience of a Water Supply System under Climate Change and Population Growth Impacts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2885-2898, July.

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