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信息能源危机与经济增长关联性分析——基于系统动力学方法 被引量:1

Analysis of the Correlation of Information Energy Crisis and Economic Growth Based on System Dynamics
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摘要 信息能源的不充分、不可控、冗余、极限性带来信息能源的危机,信息能源不断地膨胀与使用效率的复杂关系也暗示了信息能源危机的存在。采用CNNIC(中国互联网信息中心)发布的2006至2010年数据,设计信息能源危机变量,进行回归,确定变量间关系的方程式,进一步构建了信息能源危机与经济增长演化的系统动力学模型。研究表明,未来信息能源危机的快速增长将抑制经济的快速增长,并预测在忽略其他经济刺激因素下,受信息能源危机影响,未来经济将保持缓慢增长,甚至达到临界点。 Information energy is an information network set that consisted of substantial information elements exist- ing in a variety of network platforms have directly or indirectly effects on economic product. It is a virtual form of energy, not only renewable but also creative. The insufficiency, uncontrollability, redundancy and limit of infor- marion energy go to information energy crisis and the complex relationship between expansion of information ener- gy and efficiency of adopting it go to crisis too. This paper uses the data of CNNIC (2006-2010) and others, and then constructs the variables and regresses to determine the equation of the relationship between variables, fur- ther construct the system dynamical evolution model on the correlation of the information energy crisis and eco- nomic growth. The conclusion of research is the rapid growth of information energy crisis will inhibit the rapid economic growth in the future, and predicts that the future economic growth will remain slowly, and even reach a critical point, under without considering other measures of stimulating the economy
出处 《科学学与科学技术管理》 CSSCI 北大核心 2013年第2期86-94,共9页 Science of Science and Management of S.& T.
基金 国家自然科学基金面上项目(70372070 71171054) 福建省中国特色社会主义理论体系研究中心项目(2010D12)
关键词 信息能源危机 经济增长 关联性 系统动力学 information energy crisis economic growth association system dynamics
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参考文献23

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同被引文献7

  • 1中国互联网络信息中心.中国互联网络发展状况统计报告(2013年1月)[R].2013:33-34.
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  • 6Leski J. , Czogala E. A new artificial neural network based fuzzy inference system with moving consequents in if - then rules and selected applications [ J ]. Fuzzy Sets and Sys- tems,1999, 108(3) : 289 -297.
  • 7S.M. Taheri, R. Azizi. On information energy of the im- age fuzzy sets [ J ]. Information Sciences, 2007,177 ( 18 ) .. 3871 -3881.

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