Discussion of “Evapotranspiration Modeling Using Second-Order Neural Networks” by Sirisha Adamala, N. S. Raghuwanshi, Ashok Mishra, and Mukesh K. Tiwari
This article is a reply.
VIEW THE ORIGINAL ARTICLEThis article is a reply.
VIEW THE ORIGINAL ARTICLEThis article has a reply.
VIEW THE REPLYPublication: Journal of Hydrologic Engineering
Volume 20, Issue 9
![First page of PDF](/cms/10.1061/(ASCE)HE.1943-5584.0001208/asset/8c32d83c-ebef-4330-8f2d-c761cc8ce8bf/assets/(asce)he.1943-5584.0001208.fp.png)
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors are grateful to the Institut Valencià d’Investigacions Agràries (IVIA) for providing the meteorological data set used in the present work. P. Martí acknowledges the financial support of the research grant Juan de la Cierva JCI-2012-13513 (Spanish Ministry of Economy and Competitiveness). E. Fuster Garcia acknowledges the financial support from the Torres Quevedo program (Spanish Ministry of Economy and Competitiveness), co-founded by the European Social Fund (PTQ-12-05693).
References
Haykin, S., ed. (1999). Neural networks. A comprehensive foundation, Prentice Hall, Upper Saddle River, NJ.
Kohavi, R. (1995). “A study of cross-validation and bootstrap for accuracy estimation and model selection.” Proc., 14th Int. Joint Conf. on Artificial Intelligence, Morgan Kaufmann, San Mateo, CA, 1137–1143.
Martí, P., and Gasque, M. (2010). “Ancillary data supply strategies for improvement of temperature-based ETo ANN models.” Agric. Water Manage., 97(7), 939–955.
Martí, P., Provenzano, G., Royuela, A., and Palau-Salvador, G. (2010a). “Integrated emitter local loss prediction using artificial neural networks.” J. Irrig. Drain. Eng., 11–22.
Martí, P., Royuela, A., Manzano, J., and Palau-Salvador, G. (2010b). “Generalization of ANN models through data supplanting.” J. Irrig. Drain. Eng., 161–174.
Martí, P., Shiri, J., Duran-Ros, M., Arbat, G., Ramírez de Cartagena, F., and Puig-Bargués, J. (2013). “Artificial neural networks vs. gene expression programming for estimating outlet dissolved oxygen in micro-irrigation sand filters fed with effluents.” Comput. Electron. Agric., 99(11), 176–185.
MATLAB version 7.4.0 [Computer software]. Natick, MA, MathWorks.
Zanetti, S. S., Sousa, E. F., Oliveira, V. P. S., Almeida, F. T., and Bernardo, S. (2007). “Estimating evapotranspiration using artificial neural network and minimum climatological data.” J. Irrig. Drain. Eng., 83–89.
Information & Authors
Information
Published In
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Sep 2, 2014
Accepted: Sep 19, 2014
Published online: Mar 20, 2015
Discussion open until: Aug 20, 2015
Published in print: Sep 1, 2015
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.