Soil moisture forecast for smart irrigation: The primetime for machine learning-Reference-Cited by-同舟云学术

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Soil moisture forecast for smart irrigation: The primetime for machine learning

Published:2022-11 Issue: Volume:207 Page:117653
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Togneri Rodrigo,Felipe dos Santos Diego,Camponogara Glauber,Nagano Hitoshi,Custódio Gilliard,Prati Ronaldo,Fernandes Stênio,Kamienski Carlos

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference107 articles.

1. Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale;Abowarda;Remote Sensing of Environment,2021

2. Agricultural irrigation scheduling for a crop management system considering water and energy use optimization;Abrishambaf;Energy Reports,2020

3. Dynamic neural network modelling of soil moisture content for predictive irrigation scheduling;Adeyemi;Sensors,2018

4. Computation of evapotranspiration with artificial intelligence for precision water resource management;Afzaal;Applied Sciences,2020

5. Agrosmart. (2021). Retrieved 11 1, 2021, from Agrosmart - Cultivo Inteligente: https://agrosmart.com.br/eng/.

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