Integrated emitter local loss prediction using artificial neural networks.

Giuseppe Provenzano, Álvaro Royuela, Pau Martí, Guillermo Palau-Salvador

Risultato della ricerca: Article

24 Citazioni (Scopus)

Abstract

This paper describes an application of artificiai neural networks (ANNs) to the prediction of Iocai Iosses from integratedemitters. First, the optimum input-output combination was determined. Then, the mapping capability of ANNs and regression models wascompared. Afterwards, a five-input ANN model, which considers pipe and emitter internai diameter, emitter length, emitter spacing, andpipe discharge, was used to develop a local losses predicting tool which was obtained from different training strategies while taking intoaccount a completely independent test set. Finally, a performance index was evaluated for tbe test emitter models studied. Emitter datawith Iow reliability were removed from the processo Performance indexes over 80% were obtained for the remaining test emitters.
Lingua originaleEnglish
pagine (da-a)11-22
Numero di pagine12
RivistaJOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING
Volume136
Stato di pubblicazionePublished - 2010

All Science Journal Classification (ASJC) codes

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

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