Determination of Optimal Predictors and Sampling Frequency to Develop Nutrient Soft Sensors Using Random Forest

Despite advancements in sensor technology, monitoring nutrients in situ and in real-time is still challenging and expensive. Soft sensors, based on data-driven models, offer an alternative to direct nutrient measurements. However, the high demand for data required for their development poses logisti...

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Detalles Bibliográficos
Autores principales: Arhab, Muhammad, Huang, Jingshui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346477/
https://www.ncbi.nlm.nih.gov/pubmed/37447905
http://dx.doi.org/10.3390/s23136057

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346477/
https://www.ncbi.nlm.nih.gov/pubmed/37447905
http://dx.doi.org/10.3390/s23136057

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