Generative adversarial networks for detecting contamination events in water distribution systems using multi-parameter, multi-site water quality monitoring

Contamination events in water distribution networks (WDNs) can have a huge impact on water supply and public health; increasingly, online water quality sensors are deployed for real-time detection of contamination events. Machine learning has been used to integrate multivariate time series water qua...

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Detalles Bibliográficos
Autores principales: Li, Zilin, Liu, Haixing, Zhang, Chi, Fu, Guangtao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791317/
https://www.ncbi.nlm.nih.gov/pubmed/36578363
http://dx.doi.org/10.1016/j.ese.2022.100231

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791317/
https://www.ncbi.nlm.nih.gov/pubmed/36578363
http://dx.doi.org/10.1016/j.ese.2022.100231

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