The conventional grey GM(2,1)model built for the fast growing time sequence generally has big errors.To improve the modeling precision,the paper improves from the following two aspects:First,the paper transforms the a...The conventional grey GM(2,1)model built for the fast growing time sequence generally has big errors.To improve the modeling precision,the paper improves from the following two aspects:First,the paper transforms the accumulated generating sequence of original time sequence quantitatively to make the transformed time sequence have the better adaptability to the model;second,the paper extends the conventional grey GM(2,1)model’s structure to make the extended model meet the variation law of fast growing sequence better.The extended grey model is called the GM(2,1,Σexp(ct))model.The paper offers the parameter optimization method and the solving method of time response sequence of GM(2,1,Σexp(ct))model.Using the model and methods proposed,the paper builds the GM(2,1,Σexp(ct))models for the natural gas consumption of China and Chongqing City,China,respectively.Results show that the models built have high simulation precision and prediction precision.展开更多
基金Supported by National Natural Science Foundation of China(11401418)。
文摘The conventional grey GM(2,1)model built for the fast growing time sequence generally has big errors.To improve the modeling precision,the paper improves from the following two aspects:First,the paper transforms the accumulated generating sequence of original time sequence quantitatively to make the transformed time sequence have the better adaptability to the model;second,the paper extends the conventional grey GM(2,1)model’s structure to make the extended model meet the variation law of fast growing sequence better.The extended grey model is called the GM(2,1,Σexp(ct))model.The paper offers the parameter optimization method and the solving method of time response sequence of GM(2,1,Σexp(ct))model.Using the model and methods proposed,the paper builds the GM(2,1,Σexp(ct))models for the natural gas consumption of China and Chongqing City,China,respectively.Results show that the models built have high simulation precision and prediction precision.
