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From data to interpretable models: machine learning for soil moisture forecasting
Soil moisture is critical to agricultural business, ecosystem health, and certain hydrologically driven natural disasters. Monitoring data, though, is prone to instrumental noise, wide ranging extrema, and nonstationary response to rainfall where ground conditions change. Furthermore, existing soil...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer International Publishing
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9427440/ https://www.ncbi.nlm.nih.gov/pubmed/36060709 http://dx.doi.org/10.1007/s41060-022-00347-8 |