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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2023
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| 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 |