Predicting the upshot of covid-19 on crude-oil prices in nigeria using mlparima model
5th International Conference on Information Technology for Education and Development, ITED 2022
; 2022.
Article
Dans Anglais
| Scopus | ID: covidwho-2248413
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. © 2022 IEEE.
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
Scopus
Type d'étude:
Étude pronostique
langue:
Anglais
Revue:
5th International Conference on Information Technology for Education and Development, ITED 2022
Année:
2022
Type de document:
Article
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