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- Title
Performance evaluation of a variable rate application (VRA) system by artificial neural network (ANN) models.
- Authors
Bagheri, Nikrooz; Eyvani, Afshin; Tarabi, Nazilla
- Abstract
To evaluate the performance of a variable rate boom sprayer, an artificial neural network (ANN) was employed. To model output flow of nozzles, 727 nets by four neural net models, namely, linear, MLP, RBF and GRNN were tested. For each nozzle, 45, 22 and 23 experimental data were used for train, verification and test, respectively. The results indicated that RBF model as the best by regression ratio at 0.2 and coefficient of determination (R2) at 0.98. Based on the results, average value of R2 and coefficient of variation (CV) for RBF model were 0.99 and 18.96%, respectively. From the results, it is concluded that ANN model could be a good predictor to evaluate the performance of a variable rate application system.
- Subjects
ARTIFICIAL neural networks; VARIABLE-rate codes; NOZZLES; RADIAL basis functions; REGRESSION analysis
- Publication
Agricultural Engineering International: CIGR Journal, 2014, Vol 16, Issue 4, p105
- ISSN
1682-1130
- Publication type
Article