Hyperparameter Optimization of a Convolutional Neural Network Model for Pipe Burst Location in Water Distribution Networks

The current paper presents a hyper parameterization optimization process for a convolutional neural network (CNN) applied to pipe burst locations in water distribution networks (WDN). The hyper parameterization process of the CNN includes the early stopping termination criteria, dataset size, datase...

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Detalles Bibliográficos
Autores principales: Antunes, André, Ferreira, Bruno, Marques, Nuno, Carriço, Nelson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10052689/
https://www.ncbi.nlm.nih.gov/pubmed/36976119
http://dx.doi.org/10.3390/jimaging9030068

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10052689/
https://www.ncbi.nlm.nih.gov/pubmed/36976119
http://dx.doi.org/10.3390/jimaging9030068

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