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Urban Water Journal Volume 14, 2017 - Issue 4
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Research Articles

Stochastic data mining tools for pipe blockage failure prediction

Pedro SantosLNEC: National Civil Engineering Laboratory, Avenida do Brasil, Lisboa, Portugal;Department of Mathematics and CEMAT, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, Lisboa, Portugal
,
Conceição AmadoDepartment of Mathematics and CEMAT, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, Lisboa, Portugal
,
Sérgio T. CoelhoLNEC: National Civil Engineering Laboratory, Avenida do Brasil, Lisboa, Portugal
&
João P. LeitãoLNEC: National Civil Engineering Laboratory, Avenida do Brasil, Lisboa, Portugal;Eawag: Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, SwitzerlandCorrespondence[email protected]
Pages 343-353 | Received 12 Feb 2015, Accepted 25 Jan 2016, Published online: 21 Mar 2016

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Mojtaba Barzegar Hamzekolae, Mohammadreza Jalili Ghazizadeh, Mohammadreza Majdzadeh Tabatabai, Iman Moslehi & Ehsan Yousefi-Khoshqalb. (2023) Developing a new methodology for wastewater pipes cleaning prioritization using integrating Induced Ordered Weighted Averaging and fuzzy logic methods. Urban Water Journal 20:5, pages 521-531.
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Daniel Winkler, Markus Haltmeier, Manfred Kleidorfer, Wolfgang Rauch & Franz Tscheikner-Gratl. (2018) Pipe failure modelling for water distribution networks using boosted decision trees. Structure and Infrastructure Engineering 14:10, pages 1402-1411.
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John E. Fontecha, Puneet Agarwal, María N. Torres, Sayanti Mukherjee, Jose L. Walteros & Juan P. Rodríguez. (2021) A Two‐Stage Data‐Driven Spatiotemporal Analysis to Predict Failure Risk of Urban Sewer Systems Leveraging Machine Learning Algorithms. Risk Analysis 41:12, pages 2356-2391.
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Antonio Gálvez, Alberto Diez-Olivan, Dammika Seneviratne & Diego Galar. (2021) Fault Detection and RUL Estimation for Railway HVAC Systems Using a Hybrid Model-Based Approach. Sustainability 13:12, pages 6828.
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E. Okwori, M. Viklander & A. Hedström. (2021) Spatial heterogeneity assessment of factors affecting sewer pipe blockages and predictions. Water Research 194, pages 116934.
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N. Caradot, Ph. R. Sampaio, A. S. Guilbert, H. Sonnenberg, V. Parez & V. Dimova. (2021) Using deterioration modelling to simulate sewer rehabilitation strategy with low data availability. Water Science and Technology 83:3, pages 631-640.
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Xiatong Cai, Abdolmajid Mohammadian & Hamidreza Shirkhani. (2020) An Efficient Framework for Multi-Objective Risk-Informed Decision Support Systems for Drainage Rehabilitation. Mathematical and Computational Applications 25:4, pages 73.
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Roberto Ramirez, David Torres, P. Amparo López-Jimenez & Ricardo Cobacho. (2020) A Front-Line and Cost-Effective Model for the Assessment of Service Life of Network Pipes. Water 12:3, pages 667.
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E. Okwori, M. Viklander & A. Hedström. (2020) Performance assessment of Swedish sewer pipe networks using pipe blockage and other associated performance indicators. H2Open Journal 3:1, pages 46-57.
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Eliana Soriano Pulido, Carlos Valencia Arboleda & Juan Pablo Rodríguez Sánchez. (2019) Study of the spatiotemporal correlation between sediment-related blockage events in the sewer system in Bogotá (Colombia). Water Science and Technology 79:9, pages 1727-1738.
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Hristos Tyralis, Georgia Papacharalampous & Andreas Langousis. (2019) A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources. Water 11:5, pages 910.
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Eliana Soriano Pulido, Carlos Valencia Arboleda & Juan Pablo Rodríguez Sánchez. 2019. New Trends in Urban Drainage Modelling. New Trends in Urban Drainage Modelling 869 873 .
María Molinos-Senante, Guillermo Donoso, Ramon Sala-Garrido & Andrés Villegas. (2018) Benchmarking the efficiency of the Chilean water and sewerage companies: a double-bootstrap approach. Environmental Science and Pollution Research 25:9, pages 8432-8440.
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