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Deep Learning for Hourly FAO-56 PM-Derived Crop Evapotranspiration Estimation Using a Transformer Encoder Approach for Data-Driven Irrigation Management in Tropical Horticulture.

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Title: Deep Learning for Hourly FAO-56 PM-Derived Crop Evapotranspiration Estimation Using a Transformer Encoder Approach for Data-Driven Irrigation Management in Tropical Horticulture.
Authors: Thongnim, Pattharaporn1 (AUTHOR) pattharaporn@buu.ac.th, Wongjeam, Sirawit1 (AUTHOR)
Source: AgriEngineering. Jun2026, Vol. 8 Issue 6, p207. 21p.
Database: Academic Search Ultimate
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  Data: Deep Learning for Hourly FAO-56 PM-Derived Crop Evapotranspiration Estimation Using a Transformer Encoder Approach for Data-Driven Irrigation Management in Tropical Horticulture.
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  Data: <searchLink fieldCode="JN" term="%22AgriEngineering%22">AgriEngineering</searchLink>. Jun2026, Vol. 8 Issue 6, p207. 21p.
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        Value: 10.3390/agriengineering8060207
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        Text: English
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        PageCount: 21
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      – TitleFull: Deep Learning for Hourly FAO-56 PM-Derived Crop Evapotranspiration Estimation Using a Transformer Encoder Approach for Data-Driven Irrigation Management in Tropical Horticulture.
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              Text: Jun2026
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