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The Study Of Shenzhen Import And Output Prediction Model Based On Combined Forecast

Posted on:2014-11-02Degree:MasterType:Thesis
Country:ChinaCandidate:S BaiFull Text:PDF
GTID:2309330452469932Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Since the reform and opening up, due to the special location, good strategy,rapiddevelopment of economy and rapid increase of economic aggregate, the import andexport trade of Shenzhen increase rapidly, total volume of import and output tradehas reached100billion dollars, which has topped number1for several years. On thebasis of analysis the situation of Shenzhen import and output, combine Shenzheneconomy indicator, the article analysis and studies predict method of Shenzhen importand output trade.Firstly,the article introduces Shenzhen import and output profile, it analysis thecharacter of Shenzhen import and output trade from the structural optimization ofimport and export merchandize, the structural of market and mode of trade. Next, itdiscusses the application of factor analysis method on the Shenzhen import and exportImpact Index. On the basis of study of the correlation across Shenzhen import anoutput indicators, factor analysis method is employ to abstract4main factors whichcontain99%explanation. Then, it introduces the signal prediction method andcombined prediction method, it discusses the ARMA model, AR model, MAmodel,neural model and SVM. Lastly, the article discusses Shenzhen import andexport predict method based on combine prediction method. On the basis of dataanalysis, ARAM,BP and SVM is employed to predict separately, then weights ofsignal predictor is optimized through combination predict method. With the signalpredictor weights, it get high precise comprehensive forecast result.The study of the article shows that, combination method can predict Shenzhenimport and export trade precisely, it provides a new method for the prediction ofShenzhen import and export trade.
Keywords/Search Tags:Shenzhen, import and export, combination predict, factor analysis
PDF Full Text Request
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