摘要
灰色预测模型适用于不确定性系统,它的离散模型DGM(1,1)模型和DNGM(1,1)模型都被认为是通用的时间序列预测模型,且都能实现对齐次指数序列的无偏模拟。分别利用DGM(1,1)模型和DNGM(1,1)模型对中国能源消耗总量统计数据进行建模,通过比较2种模型对数据的模拟精度,发现DNGM(1,1)模型预测效果更好。最后,利用DNGM(1,1)模型预测到中国2022年、2023年的能源消耗总量分别为5.064 457 522×10^(9)t,5.137 593 946×10^(9)t。比较了中国一次能源生产总量与能源消耗总量的增长速度,从可持续发展的角度分析了一次能源生产与能源消耗的关系。
Grey prediction models are suitable for uncertain systems and its discrete DGM(1,1)model and DNGM(1,1)model are recognized as a versatile time series forecasting model,and both of them can realize unbiased simulation of approximately inhomogeneous exponential sequence.In this paper,DGM(1,1)model and DNGM(1,1)model were respectively used to predict the total energy consumption in China.By comparing the data simulation accuracy of the two models,it showed that DNGM(1,1)model has better prediction effect.So,the DNGM(1,1)model was used to predict the total annual energy consumption in China in 2022 and 2023,the prediction results respectively will be 5.064 457 522×10^(9)t,5.137 593 946×10^(9)t.It also compared the growth rate of total primary energy production and total energy consumption in China,and from the perspective of sustainable development,it analyzed the relationship between primary energy production and energy consumption.
作者
韩静
刘西林
王辉
李辉
HAN Jing;LIU Xilin;WANG Hui;LI Hui(School of Mathematics and Physics,Anshun University,Anshun 561000,Guizhou,China;College of Data Science,Taiyuan University of Technology,Jinzhong 030600,Shanxi,China)
出处
《能源与节能》
2023年第1期1-5,共5页
Energy and Energy Conservation
基金
贵州省教育厅自然科学研究资助项目(黔教合KY字[2018]337,[2018] 070,[2019] 069)
安顺学院博士基金项目[asxybsjj(202203)号]。
