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Urban Water Journal Volume 16, 2019 - Issue 9
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Research Articles

Pipe failure rate prediction in water distribution networks using multivariate adaptive regression splines and random forest techniques

Akbar ShirzadFaculty of Civil Engineering, Urmia University of Technology, Urmia, IranCorrespondence[email protected]
&
Mir Jafar Sadegh SafariDepartment of Civil Engineering, Yaşar University, Izmir, TurkeyCorrespondence[email protected]
Pages 653-661 | Received 08 Jul 2019, Accepted 05 Jan 2020, Published online: 23 Jan 2020

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Ahmed A. Abokifa & Lina Sela. (2023) Integrating spatial clustering with predictive modeling of pipe failures in water distribution systems. Urban Water Journal 20:4, pages 465-476.
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David Valis, Zdenek Vintr, Kamila Hasilova & Marie Forbelska. (2022) Reliability assessment of water distribution network using specific forms of state space models. Urban Water Journal 19:2, pages 109-118.
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Babak Aslani, Shima Mohebbi & Hana Axthelm. (2021) Predictive analytics for water main breaks using spatiotemporal data. Urban Water Journal 18:6, pages 433-448.
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Salman Tariq, Beenish Bakhtawar & Tarek Zayed. (2022) Data-driven application of MEMS-based accelerometers for leak detection in water distribution networks. Science of The Total Environment 809, pages 151110.
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Gema Sakti Raspati, Stian Bruaset, Camillo Bosco, Lars Mushom, Birgitte Johannessen & Rita Ugarelli. (2022) A Risk-Based Approach in Rehabilitation of Water Distribution Networks. International Journal of Environmental Research and Public Health 19:3, pages 1594.
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Mónica Marcela Giraldo-González & Juan Pablo Rodríguez. (2020) Comparison of Statistical and Machine Learning Models for Pipe Failure Modeling in Water Distribution Networks. Water 12:4, pages 1153.
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