New machine learning approaches to improve reference evapotranspiration estimates using intra-daily temperature-based variables in a semi-arid region of Spain-Reference-Cited by-同舟云学术

New machine learning approaches to improve reference evapotranspiration estimates using intra-daily temperature-based variables in a semi-arid region of Spain

Published:2021-02 Issue: Volume:245 Page:106558
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

Bellido-Jiménez Juan Antonio,Estévez Javier,García-Marín Amanda Penélope

Funder

Universidad de Córdoba

Spanish National Plan for Scientific and Technical Research and Innovation

Publisher

Elsevier BV

Subject

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

Reference98 articles.

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4. Akusok, A., Björk, K.-M., Miche, Y., Lendasse, A., 2015. High performance extreme learning machines: a complete toolbox for big data applications. Access, IEEE, pp.1-1, doi: 10.1109/ACCESS.2015.2450498.

5. Allen, R., Pereira, L., Smith, M., 1998. Crop evapotranspiration-Guidelines for computing crop water requirements, FAO Irrigation and Drainage.

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