Grey prediction with rolling mechanism for electricity demand forecasting of Turkey

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Forecasting iron ore import and consumption of China using grey model optimized by particle swarm optimization algorithm (2013, methodology): “Akay (2007) employed a rolling mechanism to increase the forecasting accuracy of GM in the case of exponential and chaotic data.”
Natural gas demand in Turkey (2009, unknown): “mechanism (GPRM) Akay and Atak [45]”
Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China (2012, methodology): “Akay and Atak (2007) adopted the Grey prediction with the rolling mechanism (GPRM) approach to forecast Turkey’s total and industrial electricity consumption.”
Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025 (2008, methodology): “Akay and Atak (2007) proposed an approach using gray prediction with rolling mechanism (GPRM) to predict the Turkey’s total and industrial electricity consumption.”
Forecast of electricity consumption and economic growth in Taiwan by state space modeling (2009, background): “Articles [27] and [28] presented a trigonometric grey prediction approach and a grey prediction with rolling mechanism approach to forecast electricity demand in China and Turkey, respectively.”