CSA  >> Vol. 4 No. 12 (December 2014)

    基于经济指标的信息熵能源总量多因子控制模型构建
    Building of Energy Consumption Multi-Factor Control Model with Economic Indicator Based on Information Entropy

  • 全文下载: PDF(486KB) HTML    PP.369-378   DOI: 10.12677/CSA.2014.412049  
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作者:  

宋金城:盐城工业职业技术学院机电工程学院,盐城

关键词:
信息熵消费结构经济指标多因子控制模型Information Entropy Consumption Structure Economic Indicators Multi-Factor Control Model

摘要:

针对如何合理分配与控制能源消费总量是保障能源安全的关键问题,该文首先提出了产业结构、科技水平、能源消费结构、资源禀赋和人民生活水平等经济指标构建的方法,得出产业机构和科技水平两个因子对原始数据总方差的贡献率分别为42.7006%和41.4781%,累计贡献率达到了84.1786%的结论;进而依据能量消费总量、地区生产总值、工业增加值、地方财政一般预算支出、地方财政一般预算收入、社会消费品零售总额、消费物价指数和城镇居民人均可支配收入等经济指标,利用信息熵测度不确定性提出了基于信息熵的多因子能源总量控制方法,实验结果表明,其产业结构对能源消耗的贡献率为42.7006%,信息熵分配与实际能源分配之间校验误差在0.00244以内,符合各省市能量分配数据实际情况,为全国各省市能能源分配与控制提供了可靠的决策支持依据。

How to rationally allocate energy consumption is a key issue of energy security. A new model is given to solve this problem. First, A method of constructing the industrial structure, technological level, energy consumption structure, resource endowments, people’s living standards and other economic indicators is given, and we draw conclusions that the contribution rates of factors of in-dustrial organization and technological level are 42.7006% and 41.4781% and that the cumulative contribution rate is 84.1786%. The energy consumption multi-factor control method with economic indicator based on information entropy is given with the total amount of energy con- sumption, regional production, the value of the industrial growth, local general budget expendi- tures, local general budget revenues, total retail sales of social consumer goods, consumer price index and per capita disposable income of urban residents and other economic indicators, based on the uncertainty of information entropy. The result shows that the contribution of industrial structure of energy consumption rate is 42.7006%, and that the parity error between the actual energy distribution and the actual entropy distribution is 0.00244, which is in line with the actual situation of energy distribution with data in the provinces, and provides a reliable basis for decision support.

文章引用:
宋金城. 基于经济指标的信息熵能源总量多因子控制模型构建[J]. 计算机科学与应用, 2014, 4(12): 369-378. http://dx.doi.org/10.12677/CSA.2014.412049

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