摘要
In grey models,GM(1,1)is an important prediction model.The grey model GM(1,1)has good prediction results in the case original data change exponentially at a low speed.However in practical cases sometimes,original data show exponential changes or approximately exponential changes change at a high speed.In these cases,the grey model GM(1,1)has poor prediction results because the data fail to meet the laws of traditional model.Therefore,the paper proposes an extended grey model GM(1,1,ebk)and its modeling method.In the final section,the paper builds grey models of GM(1,1,ebk)for a practical problem and the results show the grey model proposed has greatly improved simulation and prediction accuracy compared with the traditional model.
In grey models, GM(1,1) is an important prediction model. The grey model GM(1,1)has good prediction results in the case original data change exponentially at a low speed. However in practical cases sometimes, original data show exponential changes or approximately exponential changes change at a high speed. In these cases, the grey model GM(1,1) has poor prediction results because the data fail to meet the laws of traditional model. Therefore, the paper proposes an extended grey model GM(1, 1, ebk) and its modeling method. In the final section, the paper builds grey models of GM(1, 1, ebk) for a practical problem and the results show the grey model proposed has greatly improved simulation and prediction accuracy compared with the traditional model.
基金
Supported by the National Natural Science Foundation of China(11401418).
