Variable weight combination forecasting combines individual forecasting models after giving them proper weights at each time point. Weight is the type of function that changes with forecast time. A relatively rational...Variable weight combination forecasting combines individual forecasting models after giving them proper weights at each time point. Weight is the type of function that changes with forecast time. A relatively rational description of the system can be proposed with the forecasting method, which is of higher precision and better stability. Two individual forecasting models, grey system forecasting and multiple regression forecasting, were generated based on the historical data and influencing factors of coal demand in China from 1981 to 2008. According to the theory of combination forecasting, the variable weight combination forecasting model was formulated to forecast coal demand in China for the next 12 years.展开更多
This paper mainly discusses the nonlinear combination forecasting model and states that the nonlinear combination forecasting model is better than linear combination forecasting model in many aspect.
基金the National Natural Science Foundation in China (No.70873079 and 70941022)Shanxi Natural Science Foundation (No.2009011021-1)Shanxi International Science and Technology Cooperation Foundation (2008081014)
文摘Variable weight combination forecasting combines individual forecasting models after giving them proper weights at each time point. Weight is the type of function that changes with forecast time. A relatively rational description of the system can be proposed with the forecasting method, which is of higher precision and better stability. Two individual forecasting models, grey system forecasting and multiple regression forecasting, were generated based on the historical data and influencing factors of coal demand in China from 1981 to 2008. According to the theory of combination forecasting, the variable weight combination forecasting model was formulated to forecast coal demand in China for the next 12 years.
文摘This paper mainly discusses the nonlinear combination forecasting model and states that the nonlinear combination forecasting model is better than linear combination forecasting model in many aspect.
