Embedded Temporal Convolutional Networks for Essential Climate Variables Forecasting

Forecasting the values of essential climate variables like land surface temperature and soil moisture can play a paramount role in understanding and predicting the impact of climate change. This work concerns the development of a deep learning model for analyzing and predicting spatial time series,...

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Detalles Bibliográficos
Autores principales: Villia, Maria Myrto, Tsagkatakis, Grigorios, Moghaddam, Mahta, Tsakalides, Panagiotis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914661/
https://www.ncbi.nlm.nih.gov/pubmed/35270998
http://dx.doi.org/10.3390/s22051851

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914661/
https://www.ncbi.nlm.nih.gov/pubmed/35270998
http://dx.doi.org/10.3390/s22051851

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