Estimating wheat and maize daily evapotranspiration using artificial neural network-Reference-Cited by-同舟云学术

Estimating wheat and maize daily evapotranspiration using artificial neural network

Published:2018-02-22 Issue:3-4 Volume:135 Page:945-958
ISSN:0177-798X
Container-title:Theoretical and Applied Climatology
language:en
Short-container-title:Theor Appl Climatol

Author:

Abrishami Nazanin,Sepaskhah Ali Reza,Shahrokhnia Mohammad Hossein

Funder

Iran National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

http://link.springer.com/article/10.1007/s00704-018-2418-4/fulltext.html

Reference43 articles.

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3. Ayoubi S, Sahrawat KL (2011) Comparing multivariate regression and artificial neural network to predict barley production from soil characteristics in northern Iran. Arch Agron Soil Sci 57:549–565

4. Azadi S, Sepaskhah A (2012) Annual precipitation forecast for west, southwest, and south provinces of Iran using artificial neural networks. Theor Appl Climatol 109:175–189

5. Blaney HF, Criddle WD (1950) Determining water requirements in irrigated areas from climatological and irrigation data. U.S. Department of Agriculture, Soil Conservation Service. (Technical Report NO. 96)

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