Customised-sampling approach for pipe failure prediction in water distribution networks

Abstract This paper presents a new methodology for addressing imbalanced class data for failure prediction in Water Distribution Networks (WDNs). The proposed methodology relies on existing approaches including under-sampling, over-sampling, and class weighting as primary strategies. These technique...

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Autors principals:	Milad Latifi, Ramiz Beig Zali, Akbar A. Javadi, Raziyeh Farmani
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2024-08-01
Col·lecció:	Scientific Reports
Matèries:	Failure prediction in pipes Water distribution networks Machine learning Imbalance class data Under-sampling Over-sampling
Accés en línia:	https://doi.org/10.1038/s41598-024-69109-9
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