Data/hora: 12/06/2024 08:54:51

Provedor de dados: | 91
País: | Brazil
Título: | Artificial neural network model for simulation of water distribution in sprinkle irrigation
Autores: | Menezes,Paulo L. de; Azevedo,Carlos A. V. de; Eyng,Eduardo; Dantas Neto,José; Lima,Vera L. A. de.
Data: | 2015-09-01
Ano: | 2015
Palavras-chave: | Sprinkler; Water distribution uniformity; Artificial intelligence; Computational model.
Resumo: | ABSTRACTDetermining uniformity coefficients of sprinkle irrigation systems, in general, depends on field trials, which require time and financial resources. One alternative to reduce time and expense is the use of simulations. The objective of this study was to develop an artificial neural network (ANN) to simulate sprinkler precipitation, using the values ​​of operating pressure, wind speed, wind direction and sprinkler nozzle diameter as the input parameters. Field trials were performed with one sprinkler operating in a grid of 16 x 16, collectors with spacing of 1.5 m and different combinations of nozzles, pressures, and wind conditions. The ANN model showed good results in the simulation of precipitation, with Spearman's correlation coefficient (rs) ranging from 0.92 to 0.97 and Willmott agreement index (d) from 0.950 to 0.991, between the observed and simulated values for ten analysed trials. The ANN model shows promise in the simulation of precipitation in sprinkle irrigation systems.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662015000900817
Editor: | Departamento de Engenharia Agrícola  - UFCG
Relação: | 10.1590/1807-1929/agriambi.v19n9p817-822
Formato: | text/html
Fonte: | Revista Brasileira de Engenharia Agrícola e Ambiental  v.19 n.9 2015
Fonte: | info:eu-repo/semantics/openAccess