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Total Electricity Consumption Forecasting Based on Temperature Composite Index and Mixed-Frequency Models
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作者 Xuerong Li Wei shang +2 位作者 Xun Zhang baoguo shan Xiang Wang 《Data Intelligence》 EI 2023年第3期750-766,共17页
The total electricity consumption(TEC)can accurately reflect the operation of the national economy,and the forecasting of the TEC can help predict the economic development trend,as well as provide insights for the for... The total electricity consumption(TEC)can accurately reflect the operation of the national economy,and the forecasting of the TEC can help predict the economic development trend,as well as provide insights for the formulation of macro policies.Nowadays,high-frequency and massive multi-source data provide a new way to predict the TEC.In this paper,a"seasonal-cumulative temperature index"is constructed based on high-frequency temperature data,and a mixed-frequency prediction model based on multi-source big data(Mixed Data Sampling with Monthly Temperature and Daily Temperature index,MIDAS-MT-DT)is proposed.Experimental results show that the MIDAS-MT-DT model achieves higher prediction accuracy,and the"seasonal-cumulative temperature index"can improve prediction accuracy. 展开更多
关键词 Total electricity consumption seasonal effect temperature big data high-frequency big data mixedfrequency prediction model
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