Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm

Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm

Evapotranspiration, as a combination of evaporation and transpiration of water vapour, is a primary component of global hydrological cycles. It accounts for significant loss of soil moisture from the earth to the atmosphere. Reliable methods to monitor and forecast evapotranspiration are required fo...

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Bibliographic Details
Main Authors: W. J. M. Lakmini Prarthana Jayasinghe, Ravinesh C. Deo, Afshin Ghahramani, Sujan Ghimire, Nawin Raj
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Reference evapotranspiration forecasting
deep learning
multivariate empirical mode decomposition
boruta-random forest algorithm
long short-term memory network
Online Access:https://ieeexplore.ieee.org/document/9650850/

Internet

https://ieeexplore.ieee.org/document/9650850/

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