Markov's modified urban electricity consumption prediction model based on optimal residuals
In the process of predicting the electricity consumption of urban residents in Huzhou,the historical electricity consumption data shows strong volatility and seasonality,which leads to the unsatisfactory prediction effect of the original model.In this paper,the Markov modified combination model is introduced and improved,and the residual division part of the Markov modified residual division is improved to adaptive residual division.It was used to modify the original models of metabolism GM(1,1),SARIMA,Holt-Winters,LSTM,etc.The combined model modified by DC-Markov,MC-Markov and SC-Markov is used to predict the residential electricity consumption data of Huzhou City in the coming months.The results show that the prediction accuracy of the adaptive residual division Markov modified model proposed in this paper is improved to some extent compared with the original model,and the DC-Markov-Holt-Winters model has higher accuracy in the prediction of urban residential electricity consumption data in Huzhou City.
国家科技期刊平台
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