Forecast of short-term daily reference evapotranspiration under limited meteorological variables using a hybrid bi-directional long short-term memory model (Bi-LSTM)-Reference-Cited by-同舟云学术

Forecast of short-term daily reference evapotranspiration under limited meteorological variables using a hybrid bi-directional long short-term memory model (Bi-LSTM)

Published:2020-12 Issue: Volume:242 Page:106386
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

Yin Juan,Deng Zhen,Ines Amor V.M.,Wu Junbin,Rasu Eeswaran

Funder

Education Department of Ningxia Hui Autonomous Region

Ningxia University

Publisher

Elsevier BV

Subject

Earth-Surface Processes,Soil Science,Water Science and Technology,Agronomy and Crop Science

Reference79 articles.

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4. Short‐term precipitation forecast based on the PERSIANN system and LSTM recurrent neural networks;Akbari Asanjan;J. Geophys. Res. Atmos.,2018

5. Crop Evapotranspiration-guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56;Allen,1998

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