Grey prediction is vital in statistical prediction with wide applications.However,most grey prediction methods focus on annual predictions of the monotonic time series instead of the seasonal time series.The paper use...Grey prediction is vital in statistical prediction with wide applications.However,most grey prediction methods focus on annual predictions of the monotonic time series instead of the seasonal time series.The paper uses the extended model of the grey GM(1,1)model to predict the seasonal time series.Some improvements have been made in two aspects to improve the prediction accuracy of the model.1)We introduce seasonal multiple factors to transform the original time series,which improves the adaptability of the seasonal data to the model.The transformed series conforms to the law presented by the model.2)The seasonal data are in superimposed sine and cosine fluctuations with tendencies.Therefore,the paper extends the grey action quantity of the traditional GM(1,1)model.The newly extended grey model is called the GM(1,1,exp×sin,exp×cos)model,which is provided with the parameter optimization methods and time response equations.According to the proposed modeling method,we establish a GM(1,1,exp×sin,exp×cos)model for China's quarterly gross domestic product(GDP)with high accuracy.展开更多
基金Supported by National Natural Science Foundation of China (11401418)。
文摘Grey prediction is vital in statistical prediction with wide applications.However,most grey prediction methods focus on annual predictions of the monotonic time series instead of the seasonal time series.The paper uses the extended model of the grey GM(1,1)model to predict the seasonal time series.Some improvements have been made in two aspects to improve the prediction accuracy of the model.1)We introduce seasonal multiple factors to transform the original time series,which improves the adaptability of the seasonal data to the model.The transformed series conforms to the law presented by the model.2)The seasonal data are in superimposed sine and cosine fluctuations with tendencies.Therefore,the paper extends the grey action quantity of the traditional GM(1,1)model.The newly extended grey model is called the GM(1,1,exp×sin,exp×cos)model,which is provided with the parameter optimization methods and time response equations.According to the proposed modeling method,we establish a GM(1,1,exp×sin,exp×cos)model for China's quarterly gross domestic product(GDP)with high accuracy.
