Forecasting Foreign Direct Investment Inflow to Egypt and Determinates: Using Machine Learning Algorithms and ARIMA Model. (6th December 2021)
- Record Type:
- Journal Article
- Title:
- Forecasting Foreign Direct Investment Inflow to Egypt and Determinates: Using Machine Learning Algorithms and ARIMA Model. (6th December 2021)
- Main Title:
- Forecasting Foreign Direct Investment Inflow to Egypt and Determinates: Using Machine Learning Algorithms and ARIMA Model
- Authors:
- Abd El-Aal, Mohamed F.
Algarni, Ali
Fayomi, Aisha
Abdul Rahman, RAahayu
Alrashidi, Khudir - Other Names:
- Arif Muhammad Academic Editor.
- Abstract:
- Abstract : This study aims to determine the primary determination of FDI inflow to Egypt using machine learning algorithms and the ARIMA model and get an accurate prediction of FDI inflow to Egypt during the current decade (2020–2030) and approved that the gradient boosting model is the most accurate algorithms. Also, we find stability in economic indicators in Egypt during the current decade using the ARIMA model. The last step approved that the primary determinant of FDI inflow to Egypt is the Human Development Index, followed by population size, gross domestic product per capita, lending rate, and gross domestic product value.
- Is Part Of:
- Journal of advanced transportation. Volume 2021(2021)
- Journal:
- Journal of advanced transportation
- Issue:
- Volume 2021(2021)
- Issue Display:
- Volume 2021, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 2021
- Issue:
- 2021
- Issue Sort Value:
- 2021-2021-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12-06
- Subjects:
- Transportation -- Periodicals
388.05 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2042-3195 ↗ - DOI:
- 10.1155/2021/9614101 ↗
- Languages:
- English
- ISSNs:
- 0197-6729
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20432.xml