Short-term prediction of reference crop evapotranspiration based on machine learning with different decomposition methods in arid areas of China

Author:

Lu Yingjie,Li Tao,Hu Hui,Zeng Xuemei

Funder

Chinese Academy of Sciences

Natural Science Basic Research Program of Shaanxi Province

Publisher

Elsevier BV

Subject

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

Reference55 articles.

1. Estimating reference evapotranspiration using hybrid adaptive fuzzy inferencing coupled with heuristic algorithms;Adnan;Comput. Electron. Agric.,2021

2. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998, Crop evapotranspiration: gigelines for computing crop water requirements. In: FAO Irrgation and Drainage Paper No. 56. FAO, Rome, Italy.

3. Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5;Ausati;Atmos. Environ.,2016

4. Using b-ootstrap ELM and LSSVM models to estimate river ice thickness in the Ma-ckenzie River Basin in the Northwest Territories, Canada;Barzegar;J. Hydrol.,2019

5. Artificial neural network approach for investigating the impact of convector design parameters on the heat transfer and total weight of panel radiators;Calisir;Int. J. Therm. Sci.,2023

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