基于组合预测模型的煤炭能源消费总量预测
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摘要
文章以2000—2016年的煤炭能源消费总量为原始数据,分析改进灰色预测模型,同时引入逻辑斯蒂预测模型,以组合模型与原始数据的残差平方和最小为目标函数确定组合模型权重系数,建立组合预测模型,通过验证3者的预测结果,得出组合模型比单一预测模型预测效果更好,适用性更强,对于煤炭能源消费总量的预测具有较好的指导意义与可行性。
This paper takes the total coal energy consumption from 2000 to 2016 as the original data, analyzes the improved grey prediction model, and introduces the logistic prediction model. The weight coefficient of the combined model is determined by the minimum sum of the residuals of the combined model and the original data. The combination forecasting model is established. By verifying the prediction results of the three, the combined model is better than the single forecasting model and has better applicability. It has good guiding significance and feasibility for the prediction of total coal energy consumption.
This paper takes the total coal energy consumption from 2000 to 2016 as the original data, analyzes the improved grey prediction model, and introduces the logistic prediction model. The weight coefficient of the combined model is determined by the minimum sum of the residuals of the combined model and the original data. The combination forecasting model is established. By verifying the prediction results of the three, the combined model is better than the single forecasting model and has better applicability. It has good guiding significance and feasibility for the prediction of total coal energy consumption.
引文
[1] 徐荣辉.逻辑斯蒂方程及其应用[J].山西财经大学学报,2010,32(Z2):311-312.
[2] 代涛,黄显峰,徐学军.离散Logistic人口增长预测模型研究[J].三峡大学学报(自然科学版),2010,32(5):102-105.
[3] 张鹏丽,李育.逻辑斯蒂模型在河谷型城市洪水事件研究中的验证[J].西北师范大学学报(自然科学版),2017,53(1):128-134.
[4] 梁慧玲,王文辉,郭福涛,林芳芳,林玉蕊.比较逻辑斯蒂与地理加权逻辑斯蒂回归模型在福建林火发生的适用性[J].生态学报,2017,37(12):4128-4141.
[5] 张鑫,任永泰,王福林,付强.基于改进灰色马尔科夫模型的年降水量预测[J].数学的实践与认识,2011,41(11):51-57.
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[7] 侯翔龙,阳辉.基于滑动无偏灰色马尔科夫模型的水库年降雨量预测[J].水土保持通报,2014,34(3):181-184.
[8] 王安,杨雨.基于最小二乘法的灰色组合预测模型及其应用[J].数学的实践与认识,2018,48(22):291-299.
[9] 石端银,李文宇,蔡吉花,董志超.改进的灰色增量模型及其在哈市人口预测中的应用[J].数学的实践与认识,2013,43(10):71-76.
[10] 孙涵,周丽娜,郭海湘.中国城镇居民生活完全能源消费的测算及趋势分析[J].中国能源,2014,36(4):40-44.
[11] 向思桐,祝继常,宫薇薇.基于季节性特征分析的铁路煤炭运输预测方法[J].统计与决策,2019(5):85-88.
[12] 王鉴雪,宁云才.基于灰色理论的煤炭消费影响因素分析[J].煤炭技术,2009,28(11):193-195.
[13] 时合生,樊爱宛,王巍.用马尔可夫残差修正灰色理论的煤炭需求预测[J].计算机仿真,2011,28(10):187-190.
[14] KUMAR U ,JAIN V K .Time series models (Grey-Markov,Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India[J].Energy,2010,35(4):1709-1716.
[15] ROUT U K ,Alfred Voβ,SINGH A ,et al.Energy and emissions forecast of China over a long-time horizon[J].Energy,2011,36(1):1-11.
[2] 代涛,黄显峰,徐学军.离散Logistic人口增长预测模型研究[J].三峡大学学报(自然科学版),2010,32(5):102-105.
[3] 张鹏丽,李育.逻辑斯蒂模型在河谷型城市洪水事件研究中的验证[J].西北师范大学学报(自然科学版),2017,53(1):128-134.
[4] 梁慧玲,王文辉,郭福涛,林芳芳,林玉蕊.比较逻辑斯蒂与地理加权逻辑斯蒂回归模型在福建林火发生的适用性[J].生态学报,2017,37(12):4128-4141.
[5] 张鑫,任永泰,王福林,付强.基于改进灰色马尔科夫模型的年降水量预测[J].数学的实践与认识,2011,41(11):51-57.
[6] 李义华,杜康,周洁.基于改进灰色马尔科夫模型的木材需求量预测[J].中南林业科技大学学报(自然科学版),2017,37(12):133-138.
[7] 侯翔龙,阳辉.基于滑动无偏灰色马尔科夫模型的水库年降雨量预测[J].水土保持通报,2014,34(3):181-184.
[8] 王安,杨雨.基于最小二乘法的灰色组合预测模型及其应用[J].数学的实践与认识,2018,48(22):291-299.
[9] 石端银,李文宇,蔡吉花,董志超.改进的灰色增量模型及其在哈市人口预测中的应用[J].数学的实践与认识,2013,43(10):71-76.
[10] 孙涵,周丽娜,郭海湘.中国城镇居民生活完全能源消费的测算及趋势分析[J].中国能源,2014,36(4):40-44.
[11] 向思桐,祝继常,宫薇薇.基于季节性特征分析的铁路煤炭运输预测方法[J].统计与决策,2019(5):85-88.
[12] 王鉴雪,宁云才.基于灰色理论的煤炭消费影响因素分析[J].煤炭技术,2009,28(11):193-195.
[13] 时合生,樊爱宛,王巍.用马尔可夫残差修正灰色理论的煤炭需求预测[J].计算机仿真,2011,28(10):187-190.
[14] KUMAR U ,JAIN V K .Time series models (Grey-Markov,Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India[J].Energy,2010,35(4):1709-1716.
[15] ROUT U K ,Alfred Voβ,SINGH A ,et al.Energy and emissions forecast of China over a long-time horizon[J].Energy,2011,36(1):1-11.