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所属单位：经济与管理学院

发表刊物：PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON GREY SYSTEMS AND INTELLIGENT SERVICES (GSIS)

关键字：multi-variables grey model TMGM(1,N) driving variables convolution integral total electricity consumption

摘要：Electricity demand prediction plays an important role in the policy makings and plans for the governments, energy sector investors and other relevant stakeholders. Although there exist several forecasting techniques, selection of the most appropriate technique is of great importance. One of the forecasting techniques which has proved successful in prediction is GM(1, N). In order to clarify the interaction mechanism of driving variables and improve the accuracy of the model, a new model which is based on the development trend of multiple driving variables, abbreviated as TMGM (1, N), is proposed. Firstly, a new forecast model of the development trend of the driving variables is established in order to make better use of the interaction mechanism of the driving variables. On the basis of that, the new grey model TMGM (1, N) is constructed. Meanwhile, the solution to the model parameters are derived on the least square method. And the time response formula is solved by the convolution integral to make up the defects of the solving method of traditional model GM(1, N). Finally, a real application about the forecast of the total electricity consumption in Jiangsu Province is used to demonstrate the feasibility and practicability of the TMGM(1, N) model. The results indicate the superiority of TMGM(1, N) model when compared with GM(1, N) model and TGM(1, N) model.

是否译文：否

发表时间：2017-01-01

合写作者：丁松滨,Zhao, Kai

通讯作者：党耀国