A Markov chain grey model: A forecasting of the Philippines electric energy demand

The aim of this paper is to develop a prediction model of energy demand of the Philippines. A Markov Chain Grey Model (MCGM) is proposed to forecast the monthly energy demand of the Philippines. Data were gathered and obtained from the Department of Energy that covers a total of 17 years starting from year 2000 to 2016. The proposed Markov Chain Grey Model (MCGM) is compared to Grey Model (GM) using forecasting accuracy such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Squared Error (MSE), and Normalized Mean Square Error (NMSE). The comparison reveals that MCGM is the best model among the two models to forecast the monthly energy demand of the Philippines in the year 2017 to 2022.The aim of this paper is to develop a prediction model of energy demand of the Philippines. A Markov Chain Grey Model (MCGM) is proposed to forecast the monthly energy demand of the Philippines. Data were gathered and obtained from the Department of Energy that covers a total of 17 years starting from year 2000 to 2016. The proposed Markov Chain Grey Model (MCGM) is compared to Grey Model (GM) using forecasting accuracy such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Squared Error (MSE), and Normalized Mean Square Error (NMSE). The comparison reveals that MCGM is the best model among the two models to forecast the monthly energy demand of the Philippines in the year 2017 to 2022.