caa a22 4500 445837756 CHVBK 20180317145335.0 cr unu---uuuuu 170323e20110501xx s 000 0 eng 10.1007/s00271-010-0224-6 doi (NATIONALLICENCE)springer-10.1007/s00271-010-0224-6 Assessment of a 4-input artificial neural network for ETo estimation through data set scanning procedures [Elektronische Daten] [Pau Martí, Juan Manzano, Álvaro Royuela] Evapotranspiration is a complex and non-linear phenomenon that depends on the interaction of several climatic parameters. As an alternative to traditional techniques, artificial neural networks (ANNs) are highly appropriate for the modeling of non-linear processes. In general, in the most common ANN applications, the available climatic series are usually split up into 3 data sets: one for training, one for cross-validating, and one for testing. Up to now, the studies regarding ANN-models for reference evapotranspiration estimation and forecasting consider usually only a single chronological assignment of data for the definition of these 3 data sets. In these cases, the ANN performance can only be referred to this specific data set assignment. This paper analyzes the performance of a simple ANN model, a temperature-based 4-input ANN, taking into consideration a complete scan of the possible training, cross-validation, and test set configurations using ‘leave one out' procedures. The results of a comparative analysis between both methodologies show that the performance results achieved with the traditional methodology can be misleading when evaluating the real ability of a model, as they are referred to the single specific data set assignment assumed. Springer-Verlag, 2010 Martí Pau Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut Manzano Juan Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut Royuela Álvaro Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut Irrigation Science Springer-Verlag 29/3(2011-05-01), 181-195 0342-7188 29:3<181 2011 29 271 https://doi.org/10.1007/s00271-010-0224-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00271-010-0224-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Martí Pau Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut NATIONALLICENCE 700 1- Manzano Juan Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut NATIONALLICENCE 700 1- Royuela Álvaro Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut NATIONALLICENCE 773 0- Irrigation Science Springer-Verlag 29/3(2011-05-01), 181-195 0342-7188 29:3<181 2011 29 271 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer