A hybrid CNN-GRU model for predicting soil moisture in maize root zone-Reference-Cited by-同舟云学术

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A hybrid CNN-GRU model for predicting soil moisture in maize root zone

Published:2021-02 Issue: Volume:245 Page:106649
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

Yu Jingxin,Zhang Xin,Xu Linlin,Dong Jing,Zhangzhong Lili

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

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

Reference31 articles.

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

2. Spatial analysis methods and application of regional soil moisture;Alun;Chin. Agric. Sci. Bull.,2012

3. Daily reference evapotranspiration estimates by artificial neural networks technique and empirical equations using limited input climate variables;Antonopoulos;Comput. Electron. Agric.,2017

4. Research on soil moisture prediction model based on deep learning;Cai;PLOS One,2019

5. An efficient implementation of 2D convolution in CNN;Chang;IEICE Electron. Express,2016

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