Forecasting carbon dioxide emissions for Malaysia using grey model with Cramer's rule
This article analyses and forecasts carbon dioxide (CO#) emissions in Malaysia for the 2014 to 2018 period. The study analysed the data using grey forecasting model with Cramer's rule to calculate the best SOGM(2,1) model with the highest accuracy of precision compared to conventional grey fore...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit UTM Press
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/26623/1/AniShabri2021_ForecastingCarbonDioxideEmissions.pdf http://eprints.utm.my/id/eprint/26623/ http://dx.doi.org/10.11113/MJFAS.V17N4.2091 |
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| Summary: | This article analyses and forecasts carbon dioxide (CO#) emissions in Malaysia for the 2014 to 2018 period. The study analysed the data using grey forecasting model with Cramer's rule to calculate the best SOGM(2,1) model with the highest accuracy of precision compared to conventional grey forecasting model. According to the forecasted result, the fitted values using SOGM(2,1) model has a higher accuracy precision with better capability in handling information to fit larger scale of uncertain feature compared to other conventional grey forecasting models. This article offers insightful information to policymakers in Malaysia to develop better renewable energy instruments to combat the greater issues of global warming and reducing the fossil carbon dioxide emissions into the environment. |
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