Prediction of irrigation water requirement based on parallel CNN-LSTM model and Mann-Kendall test
Author:
Affiliation:
1. Shenzhen University,College of Mechatronics and Control Engineering,Shenzhen,China
2. Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ),Shenzhen,China
3. Dongshen Intelligent Water Technology Company, LTD,Shenzhen,China
Funder
National Key Research and Development Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10639954/10639940/10640026.pdf?arnumber=10640026
Reference16 articles.
1. A hybrid framework for short-term irrigation demand forecasting
2. Investigation of crop evapotranspiration and irrigation water requirement in the lower Amu Darya River Basin, Central Asia
3. Estimation of irrigation water requirement and irrigation scheduling for major crops using the CROPWAT model and climatic data
4. Determination of the water requirement and crop coefficient values of sugarcane by field water balance method in semiarid region
5. Prediction of outlet dissolved oxygen in micro-irrigation sand media filters using a Gaussian process regression
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