To evaluate the performance of a variable rate boom sprayer, an artificial neural network (ANN) was employed. To\nmodel output flow of nozzles, 727 nets by four neural net models, namely, linear, MLP, RBF and GRNN were tested. For\neach nozzle, 45, 22 and 23 experimental data were used for train, verification and test, respectively. The results indicated\nthat RBF model as the best by regression ratio at 0.2 and coefficient of determination (R2) at 0.98. Based on the results,\naverage value of R2 and coefficient of variation (CV) for RBF model were 0.99 and 18.96%, respectively. From the results,\nit is concluded that ANN model could be a good predictor to evaluate the performance of a variable rate application system.
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