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Assesment of a 4-input artificial neural network for ETo etimation through data set scanning

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Assesment of a 4-input artificial neural network for ETo etimation through data set scanning

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Martí Pérez, PC.; Manzano Juarez, J.; Royuela, A. (2011). Assesment of a 4-input artificial neural network for ETo etimation through data set scanning. Irrigation Science. 29(3):181-195. doi:10.1007/s00271-010-0224-6

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/78513

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Title: Assesment of a 4-input artificial neural network for ETo etimation through data set scanning
Author:
UPV Unit: Universitat Politècnica de València. Centro Valenciano de Estudios sobre el Riego - Centre Valencià d'Estudis sobre el Reg
Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural
Issued date:
Abstract:
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 ...[+]
Subjects: ANN application , Artificial Neural Network , Artificial neural networks , Climatic parameters , Comparative analysis , Cross validation , Data sets , Leave one out , Non-linear phenomena , Nonlinear process , Reference evapotranspiration , Test sets , Traditional methodologies , Traditional techniques , Evapotranspiration , Water supply , Neural networks , Data set , Estimation method , Model test , Model validation , Numerical model , Performance assessment
Copyrigths: Cerrado
Source:
Irrigation Science. (issn: 0342-7188 ) (eissn: 1432-1319 )
DOI: 10.1007/s00271-010-0224-6
Publisher:
Springer Verlag (Germany)
Publisher version: http://dx.doi.org/10.1007/s00271-010-0224-6
Type: Artículo

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