基于GM(1,1)模型煤炭消费量预测研究  

Prediction of Coal Consumption Based on GM(1,1)Model

作　　者：王浩[1] 成玮 WANG Hao;CHENG Wei(School of Mine Safety,North China Institute of Science&Technology,Langfang 065201,Hebei,China)

机构地区：[1]华北科技学院矿山安全学院,河北廊坊065201

出　　处：《能源与节能》2023年第5期51-53,57,共4页Energy and Energy Conservation

摘　　要：准确预测中国煤炭消费量是决定煤炭供给侧改革成效的关键,合适的预测模型是准确预测的基础。通过对中国近年来煤炭消费场景和消费量的分析,发现时间序列预测模型是目前最适合的预测模型。以2004—2021年中国煤炭消费量为基础,建立了长期和短期2个GM(1,1)模型,预测了3年的中国煤炭消费量。结果表明,短期的灰色模型拟合程度好,精度达到99.36%,结果是可信的。Accurate prediction of China's coal consumption is the most important factor that determines the effect of the coal supply side reform,and an appropriate prediction model is the basis for accurate prediction.Through the analysis of China's coal consumption market and consumption history,it is found that the time series prediction model is the most suitable prediction model at present.On the basis of China's coal consumption from 2004 to 2021,this paper established two GM(1,1)models for the long term and the short term to predict China's coal consumption in three years.The results show that the short-term grey model has the better fitting degree,with an accuracy of 99.36%,and the results are reliable.

关 键 词：煤炭消费量 时间序列预测模型 GM(1 1) 

分 类 号：F426.21[经济管理—产业经济]