Forecasting Carbon Dioxide Emissions for Singapore using Grey Model with Cramer’s Rule


  • Assif Shamim Mustaffa Sulaiman Universiti Teknologi Malaysia
  • Ani Shabri Universiti Teknologi Malaysia



carbon dioxide emissions, grey forecasting model, Cramer’s rule


This article analyses and forecasts carbon dioxide () emissions in Singapore for the 2012 to 2016 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 Singapore 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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