Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer
•A novel deep learning-based machine learning model is proposed for weekly evapotranspiration forecasting.•A new feature selection algorithm (Boruta-CatBoost) is applied to determine effective lags for time series forecasting.•Three different climatic conditions within Iranian region are investigate...
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| Vydané v: | Computers and electronics in agriculture Ročník 198; s. 107121 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier B.V
01.07.2022
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| Predmet: | |
| ISSN: | 0168-1699 |
| On-line prístup: | Získať plný text |
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