Estimating Evapotranspiration Using Artificial Neural Network and Minimum Climatological Data-Reference-Cited by-同舟云学术

Estimating Evapotranspiration Using Artificial Neural Network and Minimum Climatological Data

Published:2007-04 Issue:2 Volume:133 Page:83-89
ISSN:0733-9437
Container-title:Journal of Irrigation and Drainage Engineering
language:en
Short-container-title:J. Irrig. Drain Eng.

Author:

Zanetti S. S.¹²³²²,Sousa E. F.¹²³²²,Oliveira V. P.¹²³²²,Almeida F. T.¹²³²²,Bernardo S.¹²³²²

Affiliation:

1. CNPq Grantee, Northern Rio de Janeiro State Univ., Campos dos Goytacazes, Rio de Janeiro, Brazil.

2. Professor, Northern Rio de Janeiro State Univ., Campos dos Goytacazes, Rio de Janeiro, Brazil.

3. Professor, Federal Center of Technological Education of Campos, Campos dos Goytacazes, Rio de Janeiro, Brazil.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Agricultural and Biological Sciences (miscellaneous),Water Science and Technology,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-9437%282007%29133%3A2%2883%29

Reference22 articles.

1. Allen R. G. Pereira L. S. Raes D. and Smith M. (1998). “Crop evapotranspiration: Guidelines for computing crop water requirements.” FAO Irrigation and Drainage Paper 56 Food and Agricultural Organization of the United Nations (FAO) Rome.

2. Arca B. Beniscasa F. and Vincenzi M. (2004). “Evaluation of neural network techniques for estimating evapotranspiration.” National Research Council ⟨http://server.ss.ibimet.cnr.it/~arcal/papers/Evaluation%20of%20neural%20newtork%20techniques%20for%20estimating%20evapotranspiration_EANN_2001.pdf⟩ (July 2 2004).

3. Avaliação do desempenho de diferentes métodos de estimativa da evapotranspiração potencialno Estado de São Paulo, Brazil;Camargo A. P.;Revista Brasileira de Agrometeorologia,1997

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