New memory-based hybrid model for middle-term water demand forecasting in irrigated areas-Reference-Cited by-同舟云学术

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New memory-based hybrid model for middle-term water demand forecasting in irrigated areas

Published:2023-06 Issue: Volume:284 Page:108367
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

González Perea R.,Fernández García I.,Camacho Poyato E.,Rodríguez Díaz J.A.

Funder

Agencia Estatal de Investigación

Ministerio de Ciencia e Innovación

Publisher

Elsevier BV

Subject

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

Reference41 articles.

1. TensorFlow: large-scale machine learning on heterogeneous distributed systems;Abadi;Netw.: Comput. Neural Syst.,2015

2. Computation of evapotranspiration with artificial intelligence for precision water resource management;Afzaal;Appl. Sci.,2020

3. FORETo: new software for reference evapotranspiration forecasting;Ballesteros;J. Arid Environ.,2016

4. Chollet, F., 2015. Keras Api documentation.

5. Water and energy footprint of irrigated agriculture in the Mediterranean region;Daccache;Environ. Res. Lett.,2014

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