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《Journal of Chengdu University of Technology(Science & Technology Edition)》 2014-05
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Gray dynamic model based on compressed sensing and its application to prediction of air cargo volume

YOU Qing-shan;XU Hai-wen;LEI Kai-hong;College of Computer Science and Technology,Civil Aviation Flight University of China;School of Electronic Engineering,University of Electronic Science and Technology of China;  
This paper studies the influence of the economic emergency on the air cargo volume.The sparse matrix can be recovered by compressed sensing,and the low-rank matrix can be recovered by a gray dynamic model.According to the air cargo volume statistical data in China from the year 2002to2009,an air cargo volume gray dynamic model based on compressed sensing is established by the CVX tool box.By comparing the true value and fitted value of the air cargo volume,the gray dynamic model can not only recover the variation tendency of the air cargo volume,but also recover the seasonal fluctuation of the air cargo volume,and even can recover the sparse influence of the economic emergency.The predicted value of the air cargo volume of 2010 is also provided.The maximum error is 5.92%.This result tells us the gray dynamic model based on compressed sensing of the air cargo volume can be used to forecast the short-term aeronautic cargo capacity,and even can provide some effective theory evidence to supervise the native aeronautic cargo market.
【Fund】: 国家自然科学民航联合基金资助项目(U1233105)
【CateGory Index】: O29;F562
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