Crude oil export: A comparative analysis using artificial neural network and ARIMA

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Abstract

The key purpose of this study is to examine the forecasting of total annual crude oil export of the Kingdom of Saudi Arabia. The present paper is based on Secondary data taken from annual reports of Saudi Arabian Monetary Authority (SAMA). The ANN and ARIMA models for forecasting are the important tools and techniques in order to illustrate the superior growth in the economy of the country. In this study, “ANN” and “Autoregressive Integrated Moving Average models” (ARIMA) have been used for predicting the total annual crude oil export of the Kingdom of Saudi Arabia. With the help of statistical software, this study tries to predict a time series data by illustrating the ANN and ARIMA models on total annual crude oil export. The total annual crude oil export of the Kingdom is gradually increasing after the year 2003. This research shall benefit the Government Administration to study about crude oil export. The outcomes of the study present that ANN model is better to predict the total annual crude oil export of the Kingdom. This study provides an insight into the position of forecasting the total annual crude oil export. The Government organization can be applied this study in making the strategic plans.

Original languageEnglish
Pages (from-to)2546-2550
Number of pages5
JournalInternational Journal of Advanced Trends in Computer Science and Engineering
Volume8
Issue number5
DOIs
StatePublished - 1 Sep 2019

Keywords

  • ANN
  • ARIMA
  • Crude Oil
  • Forecasting
  • Kingdom of Saudi Arabia

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