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《Journal of China University of Geosciences(Social Sciences Edition)》 2007-06
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The Forecasting of China's Oil Demand Based on Fusion of Soft Computing and Hard Computing

GUO Hai-xiang,ZHU Ke-jun,LI Yue,WANG De-yun(College of Management,China University of Geosciences,Wuhan 430074,China)  
Nowadays,with the rapid development of China's economy,as an important strategic resource,oil plays a more and more important role in the economic development.This paper applies the fusion of soft computing and hard computing to the forecasting of China's oil demand from 2004 to 2015 year.Firstly,it presents the cascaded pattern of fusion of soft computing and hard computing,and then,sets up the main indexes affecting oil demand,viz.GDP,population,energy sources wastage,standard of living and oil consumption.By analyzing the data features of these indexes,it obtains their jack-up trend of time process.According to this conclusion,the cascaded pattern of soft computing and hard computing will be applied: using Gompertz curve of hard computing to forecast the value of these five indexes from 2004 to 2015,and then,on the basis of these data,applying BP Network of soft computing to forecasting the oil demand from 2004 to 2015 in China.Finally,the paper takes the weighted average of the oil demands from HC forecasting and SC forecasting as the final forecasting result.
【Fund】: 国家自然科学基金资助项目(70573101);; 中国地质大学(武汉)资源环境经济研究中心开放基金资助;; 中国地质大学(武汉)优秀青年教师资助计划资助项目(CUGQNW0702)
【CateGory Index】: F426.22
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