PREDICTING THE UPSHOT OF COVID-19 ON CRUDE-OIL PRICES IN NIGERIA USING MLPARIMA MODEL

Cecilia Ajowho Adenusi, Olufunke Rebecca Vincent, Abayomi-Alli A., Olaniyi Mathew Olayiwola, Bakare Olawunmi Shamsudeen, Sayikanmi Titilayo Mary
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Abstract

Researchers and investors have been paying close attention to the application of Artificial Intelligence models to the economics, agriculture and other fields in recent years. This study uses a Multilayer Perceptron Artificial Neural Network to anticipate the effect of covid-19 on crude-oil prices, continuing the deep learning trend and also applied the use of time series model known as Autoregressive Integrated Moving Average (ARIMA) to validate the result gotten from MLP-ANN. The results produced accurately predicted crude oil prices, and covid-19 data was also analyzed, as well as the association between crude-oil prices and covid-19. Because of the substantial causative association between the coronavirus (number of confirmed cases), crude oil prices, this study is intriguing. Ten years forecast was done using both MLP-ANN and ARIMA and from result gotten, MLP-ANN has accuracy of 96% while ARIMA has 39% accuracy.
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利用mlparima模型预测2019冠状病毒病对尼日利亚原油价格的影响
近年来,研究人员和投资者一直密切关注人工智能模型在经济、农业等领域的应用。本研究使用多层感知器人工神经网络来预测covid-19对原油价格的影响,继续深度学习趋势,并使用称为自回归综合移动平均(ARIMA)的时间序列模型来验证MLP-ANN的结果。结果准确预测了原油价格,并分析了covid-19数据以及原油价格与covid-19之间的关系。由于冠状病毒(确诊病例数)与原油价格之间存在实质性的因果关系,因此这项研究很有趣。利用MLP-ANN和ARIMA进行了10年的预测,结果表明MLP-ANN的准确率为96%,ARIMA的准确率为39%。
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