Document Type : Research Paper
Abstract
The main objective of this paper is to model and forecast exports of seafood in Iran. For this purpose, the method of collective self-explanatory time series moving average (ARIMA) and artificial neural networks are used.To perform the study, monthly data for the period 1374:03 to 1387:12 estimated from model training period 1388:01 to 1390:12 data to verify the predictive power of the model used.In this study, several criteria including absolute error (MAE), mean square error (MSE), average percentage error (MAPE), root mean square error (RMSE) and root mean square normalized error (NRMSE) were used .The results of this study show better performance of the neural network predicted non-linear statistical model ARIMA models and neural network structures studied neural networks Radial Basis Function (RBF) has the best performance in terms of error functions.Finally, for the two years 1391 and 1392 the amount of exports Iranian seafood is predicted.
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