Models and explanatory variables in modelling failure for drinking water pipes to support asset management: a mixed literature review

Abstract There is an increasing demand to enhance infrastructure asset management within the drinking water sector. A key factor for achieving this is improving the accuracy of pipe failure prediction models. Machine learning-based models have emerged as a powerful tool in enhancing the predictive c...

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Autors principals:	Edwar Forero-Ortiz, Eduardo Martinez-Gomariz, Marti Sanchez-Juny, Jaume Cardus Gonzalez, Fernando Cucchietti, Ferran Baque Viader, Miquel Sarrias Monton
Format:	Artigo
Idioma:	Inglês
Publicat:	SpringerOpen 2023-10-01
Col·lecció:	Applied Water Science
Matèries:	Water distribution Water network Water pipeline failure Infrastructure asset management Pipe burst rate prediction Pipe renewal
Accés en línia:	https://doi.org/10.1007/s13201-023-02013-1
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