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

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

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%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PREDICTING THE UPSHOT OF COVID-19 ON CRUDE-OIL PRICES IN NIGERIA USING MLPARIMA MODEL
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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