dc.contributor.author | Boopathi A, Manivanna | |
dc.contributor.author | Ali EA, Mohamed | |
dc.contributor.author | Velappan, Subha | |
dc.contributor.author | A, Abudhahir | |
dc.date.accessioned | 2021-07-25T07:12:07Z | |
dc.date.available | 2021-07-25T07:12:07Z | |
dc.date.issued | 2021-07-25 | |
dc.identifier.issn | 2210-142X | |
dc.identifier.uri | https://journal.uob.edu.bh:443/handle/123456789/4311 | |
dc.description.abstract | Oil and Gas are the prime factors that play a vital role on any country’s economy, irrespective of being exported or imported. In order to ensure the economic growth of any country, it is essential for it to forecast the future need of Oil and Gas and plan the production and export accordingly. In this paper, four different types of Grey Forecasting Models namely GFM, FAGFM, MFAGFM and RGFM are developed and used to predict the future requirements of Oil and Gas production in the Kingdom of Bahrain. The official data released through Annual Report by the National Oil and Gas Authority (NOGA) of Bahrain are taken for this research. The developed Grey Forecasting Models are employed to forecast 8 most significant factors presented in the annual reports from 2010 to 2017, namely Total Oil Production, Crude Oil Imported, Crude Oil Run to Refinery+Feedstock, Refinery Production, Local Sales, Aviation Jet-fuel, Petroleum Product Export and Total Gas Production for the year 2025. The results of simulation studies are encouraging to see that the Kingdom progressing towards achieving its Vision 2030. The accuracy of forecasts are assessed using the Average Relative Percentage Error (ARPE) performance measure. | en_US |
dc.language.iso | en | en_US |
dc.publisher | University of Bahrain | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Grey Forecast Model (1,1) | en_US |
dc.subject | Rolling Grey Forecast Model (1,1) | en_US |
dc.subject | Grey Prediction | en_US |
dc.subject | Forecast accuracy | en_US |
dc.subject | Average Relative Percentage Error | en_US |
dc.subject | Firefly Algorithm | en_US |
dc.title | Forecasting Oil and Gas Production and Consumption in Kingdom of Bahrain using Optimized Grey Forecasting Models | en_US |
dc.identifier.doi | http://dx.doi.org/10.12785/ijcds/130139 | en |
dc.contributor.authorcountry | Bahrain | en_US |
dc.contributor.authorcountry | India | en_US |
dc.contributor.authorcountry | India | en_US |
dc.contributor.authorcountry | India | en_US |
dc.contributor.authoraffiliation | Bahrain Training Institute | en_US |
dc.contributor.authoraffiliation | National College of Engineering | en_US |
dc.contributor.authoraffiliation | Manonmaniam Sundaranar University & Tirunelveli, Tamilnadu | en_US |
dc.contributor.authoraffiliation | BS Abdur Rahman Crescent Institute of Science & Technology | en_US |
dc.source.title | International Journal of Computing and Digital System | en_US |
dc.abbreviatedsourcetitle | IJCDS | en_US |
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