Hybrid Deep Learning Predictor for Smart Agriculture Sensing Based on Empirical Mode Decomposition and Gated Recurrent Unit Group Model

Smart agricultural sensing has enabled great advantages in practical applications recently, making it one of the most important and valuable systems. For outdoor plantation farms, the prediction of climate data, such as temperature, wind speed, and humidity, enables the planning and control of agric...

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Detalles Bibliográficos
Autores principales: Jin, Xue-Bo, Yang, Nian-Xiang, Wang, Xiao-Yi, Bai, Yu-Ting, Su, Ting-Li, Kong, Jian-Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085784/
https://www.ncbi.nlm.nih.gov/pubmed/32121411
http://dx.doi.org/10.3390/s20051334

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085784/
https://www.ncbi.nlm.nih.gov/pubmed/32121411
http://dx.doi.org/10.3390/s20051334

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