University of Bahrain
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Forecasting Oil and Gas Production and Consumption in Kingdom of Bahrain using Optimized Grey Forecasting Models

Show simple item record Boopathi A, Manivanna Ali EA, Mohamed Velappan, Subha A, Abudhahir 2021-07-25T07:12:07Z 2021-07-25T07:12:07Z 2021-07-25
dc.identifier.issn 2210-142X
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 *
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.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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