Long-term forecasting of monthly mean reference evapotranspiration using deep neural network: A comparison of training strategies and approaches-Reference-Cited by-同舟云学术

Long-term forecasting of monthly mean reference evapotranspiration using deep neural network: A comparison of training strategies and approaches

Published:2022-09 Issue: Volume:126 Page:109221
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Chia Min Yan,Huang Yuk Feng^ORCID,Koo Chai Hoon,Ng Jing Lin^ORCID,Ahmed Ali Najah,El-Shafie Ahmed

Publisher

Elsevier BV

Subject

Software

Reference42 articles.

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3. Evaluation of the Penman-Monteith (FAO 56 PM) method for calculating reference evapotranspiration using limited data;Córdova;Mt. Res. Dev.,2015

4. Prediction of evapotranspiration by artificial neural network and conventional prediction of evapotranspiration by artificial neural network and conventional methods;Sharma;Int. J. Eng. Res.,2016

5. Recent advances in evapotranspiration estimation using artificial intelligence approaches with a focus on hybridization techniques—a review;Chia;Agronomy,2020

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