Spatial Interpolation of Soil Temperature and Water Content in the Land-Water Interface Using Artificial Intelligence

The distributed measured data in large regions and remote locations, along with a need to estimate climatic data for point sites where no data have been recorded, has encouraged the implementation of spatial interpolation techniques. Recently, the increasing use of artificial intelligence has become...

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Veröffentlicht in:	Water (Basel) 2023-02, Vol.15 (3), p.473
Hauptverfasser:	Imanian, Hanifeh, Shirkhani, Hamidreza, Mohammadian, Abdolmajid, Hiedra Cobo, Juan, Payeur, Pierre
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial intelligence Climatic data Deep learning Interpolation Machine learning Methods Moisture content Neural networks Precipitation Publishing industry Radial basis function Railroads Regression analysis Soil investigations Soil moisture Soil sciences Soil temperature Soil water Support vector machines Temperature Water content
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