dc.contributor.author | Boopathi A, Manivanna | |
dc.contributor.author | E A, Mohamed Ali | |
dc.contributor.author | Velappan, Subha | |
dc.contributor.author | A, Abudhahir | |
dc.date.accessioned | 2020-08-05T12:53:04Z | |
dc.date.available | 2020-08-05T12:53:04Z | |
dc.date.issued | 2021-04-01 | |
dc.identifier.issn | 2210-142X | |
dc.identifier.uri | https://journal.uob.edu.bh:443/handle/123456789/4057 | |
dc.description.abstract | Generation and consumption of Electricity and water are the key factors impacting the economy of any nation. Forecasting the future need of electricity and water can help the nation to plan its economy and future growth. This motivates to pursue a research to develop an efficient method to forecast the future need of Electricity and Water. In this paper, two Grey Models have been developed and employed to forecast the expected amount of generation and consumption of Electricity and Water in Kingdom of Bahrain by 2025. The past data of generation and consumption have been taken from the official statistics of Electricity and Water Authority of the Kingdom. The developed Grey Model and Modified Grey Model are used to forecast various factors such as Fuel Oil Consumption for Electricity Generation, Natural Gas Consumption for Electricity Generation, Electricity Consumption, Average Daily Production of Desalinated Water & Abstraction of Ground Water, Average Daily Water Consumption and Population for the year 2025. The results of experiments clearly show that the Kingdom is progressing towards achieving its Vision 2030. The accuracy of forecast is ensured by ensuring the least Mean Relative Percentage Error in forecasting. | 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 Model (1,1), Modified Grey Model (1,1), Grey Prediction, Mean Relative Percentage Error, Forecast accuracy | en_US |
dc.title | Forecasting the Generation and Consumption of Electricity and Water in Kingdom of Bahrain using Grey Models | en_US |
dc.identifier.doi | http://dx.doi.org/10.12785/ijcds/100139 | |
dc.volume | 10 | en_US |
dc.pagestart | 1 | en_US |
dc.pageend | 8 | en_US |
dc.source.title | International Journal of Computing and Digital Systems | en_US |
dc.abbreviatedsourcetitle | IJCDS | en_US |
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