Bayesian Sigmoid-Type Time Series Forecasting with Missing Data for Greenhouse Crops

This paper follows an integrated approach of Internet of Things based sensing and machine learning for crop growth prediction in agriculture. A Dynamic Bayesian Network (DBN) relates crop growth associated measurement data to environmental control data via hidden states. The measurement data, having...

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Detalles Bibliográficos
Autores principales: Kocian, Alexander, Carmassi, Giulia, Cela, Fatjon, Incrocci, Luca, Milazzo, Paolo, Chessa, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309099/
https://www.ncbi.nlm.nih.gov/pubmed/32517314
http://dx.doi.org/10.3390/s20113246

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309099/
https://www.ncbi.nlm.nih.gov/pubmed/32517314
http://dx.doi.org/10.3390/s20113246

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