New Accumulation Discrete Grey Model And Its Application In Energy Consumption Prediction

In recent years,the rapid development of the global economy has led to the excessive consumption of energy.In order to grasp the consumption trend of energy,it is very important to forecast the energy consumption through the prediction model.Grey prediction model is an important part of the field of minority data and poor information prediction.In order to improve the prediction accuracy of grey model,scholars have improved the model in various ways.Therefore,this paper improves the grey prediction model by solving the problem of the new information priority and the stability of the modelFirstly,this paper analyzes the research status of grey prediction theory and energy consumption prediction and expounds the related theories of the improvement methods of grey prediction model.Secondly,the modeling process and related properties of the discrete grey model and weighted accumulation grey discrete model are studied and the common limitations of the two models are found.Then,in order to solve the problems existing in the grey model,the adjacent accumulation discrete grey model is proposed and the optimal solution is found by grey wolf optimization algorithm.Finally,according to the volatility and uncertainty of the energy consumption data in APEC member countries,the adjacent accumulation discrete grey model is used to predict the energy consumption of APEC member countries.In this paper,it is found that the improvement of the accumulation method of the grey prediction model can effectively solve the problem that the traditional grey prediction model does not satisfy the new information priority and the instability of the model solution,and at the same time can improve the prediction accuracy of the model.In addition,the adjacent accumulation discrete grey model can effectively predict the volatility and uncertainty of energy consumption data.By analyzing the prediction results,the energy development of APEC can be controlled in the next few years and global energy trends can also be reflected.