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北京市能源消费与主要气象因子的突变点分析--基于灰色关联理论
引用本文:赵玥,巩在武,王文昊. 北京市能源消费与主要气象因子的突变点分析--基于灰色关联理论[J]. 南京气象学院学报, 2013, 5(4): 364-368
作者姓名:赵玥  巩在武  王文昊
作者单位:天津市津南区气象局,天津,300350;南京信息工程大学 经济管理学院,南京,210044;天津市北辰区气象局,天津,300400
基金项目:国家自然科学基金(70901043,71-171115);教育部人文社科基金(09YJC630130)
摘    要:采用灰关联分析算法,探寻北京市1980-2010年能源消费与气象因子(平均气温、降水量和日照时数等)时间序列的突变点,并将能源消费与气象因子序列进行趋势分析.结果表明:北京市能源消费序列的突变位置是1993与1997年,气象因子序列的突变位置介于1993-2000年之间;平均气温、日照时数与能源消费序列的突变位置完全相同,也即北京市气象因子与能源消费的关系极其密切.

关 键 词:灰关联分析  能源消费  气象因子  突变点  趋势分析
收稿时间:2012-02-23

Change point analysis of energy consumption and meteorological factors in Beijing:Based on gray relation theory
ZHAO Yue,GONG Zaiwu and WANG Wenhao. Change point analysis of energy consumption and meteorological factors in Beijing:Based on gray relation theory[J]. Journal of Nanjing Institute of Meteorology, 2013, 5(4): 364-368
Authors:ZHAO Yue  GONG Zaiwu  WANG Wenhao
Affiliation:Tianjin Municipal Meteordogical Bureau of Jinnan District,Tianjin 300350;School of Economics & Management,Nanjing University of Information Science & Technology,Nanjing 210044;Tianjin Municipal Meteordogical Bureau of Beichen District,Tianjin 300400
Abstract:This paper uses the method of gray relation analysis to find out the change point for time series of meteorological factors and energy consumption in Beijing from 1980 to 2010.The meteorological factors include average temperature,precipitation and sunshine hoursoutet al.It is shown that the change point of Beijing''s energy consumption series occurs in 1993 and 1997,while the change points of the meteorological factors occurs in period from 1993 to 2000.Especially,the change point of average temperature,sunshine hour and energy consumption sequences occur in the same period exactly.Furthermore,meteorological factors have the extremely close relationship with energy consumption in Beijing.In a word,according to the local climate conditions,the government could arrange the strategy of energy resource development accurately.
Keywords:gray relation analysis  energy consumption  meteorological factors  change point  trend analysis
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