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1.

Forecasting exports and imports through artificial neural network and autoregressive integrated moving average Pages 249-260 Right click to download the paper Download PDF

Authors: Teg Alam

DOI: 10.5267/j.dsl.2019.2.001

Keywords: Artificial Neural Networks (ANN), Autoregressive Integrated Moving Average (ARIMA), Forecasting, Export and Import, Kingdom of Saudi Arabia

Abstract:
Nowadays, Saudi government has established several strategic tactics such as Saudi Vision 2030 to predict the future of the country. In order to accomplish a superior growth in the economy of the country, mathematical model and forecasting techniques are important tools. In this study, total annual exports and imports of the Kingdom of Saudi Arabia are forecasted using Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) models. This paper tries to predict a time series data using ANN and ARIMA models on total annual exports and imports of Kingdom of Saudi Arabia from the year 1968 to the year 2017 with the help of statistical software XLSTAT. The applied models are used to predict some future values of total annual exports and imports of the Kingdom of Saudi Arabia. It is found that the ANN and ARIMA (1, 1, 2) and ARIMA (0, 1, 1) models are suitable for predicting the total annual exports and imports of the Kingdom of Saudi Arabia.
Details
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Journal: DSL | Year: 2019 | Volume: 8 | Issue: 3 | Views: 3972 | Reviews: 0

 

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