A Novel Groundwater Burial Depth Prediction Model Based on Two-Stage Modal Decomposition and Deep Learning

The variability of groundwater burial depths is critical to regional water management. In order to reduce the impact of high-frequency eigenmodal functions (IMF) generated by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) on the prediction results, variational modal dec...

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Detalles Bibliográficos
Autores principales: Zhang, Xianqi, Zheng, Zhiwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819980/
https://www.ncbi.nlm.nih.gov/pubmed/36612668
http://dx.doi.org/10.3390/ijerph20010345

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819980/
https://www.ncbi.nlm.nih.gov/pubmed/36612668
http://dx.doi.org/10.3390/ijerph20010345

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