a Business School, University of Shanghai for Science and Technology, Shanghai 200093, China; b College of Arts and Sciences, Shanxi Agricultural University, Taigu 030801, China

Visitor flow pattern of Expo 2010

Fan Chao^{a b}, Guo Jin-Li^{a}

a Business School, University of Shanghai for Science and Technology, Shanghai 200093, China; b College of Arts and Sciences, Shanxi Agricultural University, Taigu 030801, China

摘要 Expo 2010 Shanghai China was a successful, splendid, and unforgettable event, remaining us with valuable experiences. The visitor flow pattern of the Expo is investigated in this paper. The Hurst exponent, the mean value, and the standard deviation of visitor volume indicate that the visitor flow is fractal with long-term stability and correlation as well as obvious fluctuation in short period. Then the time series of visitor volume is converted into a complex network by using the visibility algorithm. It can be inferred from the topological properties of the visibility graph that the network is scale-free, small-world, and hierarchically constructed, confirming that the time series are fractal and a close relationship exists among the visitor volumes on different days. Furthermore, it is inevitable to have some extreme visitor volumes in the original visitor flow, and these extreme points may appear in group to a great extent. All these properties are closely related to the feature of the complex network. Finally, the revised linear regression is performed to forecast the next-day visitor volume based on the previous 10-day data.

Abstract：Expo 2010 Shanghai China was a successful, splendid, and unforgettable event, remaining us with valuable experiences. The visitor flow pattern of the Expo is investigated in this paper. The Hurst exponent, the mean value, and the standard deviation of visitor volume indicate that the visitor flow is fractal with long-term stability and correlation as well as obvious fluctuation in short period. Then the time series of visitor volume is converted into a complex network by using the visibility algorithm. It can be inferred from the topological properties of the visibility graph that the network is scale-free, small-world, and hierarchically constructed, confirming that the time series are fractal and a close relationship exists among the visitor volumes on different days. Furthermore, it is inevitable to have some extreme visitor volumes in the original visitor flow, and these extreme points may appear in group to a great extent. All these properties are closely related to the feature of the complex network. Finally, the revised linear regression is performed to forecast the next-day visitor volume based on the previous 10-day data.

基金资助:Project supported by the National Natural Science Foundation of China (Grant No. 70871082), the Shanghai Leading Academic Discipline Project, China (Grant No. S30504), and the Science and Technology Innovation Foundation of Shanxi Agricultural University, China (Grant No. 201208).

引用本文:

樊超, 郭进利 . Visitor flow pattern of Expo 2010[J]. 中国物理B, 2012, 21(7): 70209-070209.
Fan Chao, Guo Jin-Li. Visitor flow pattern of Expo 2010. Chin. Phys. B, 2012, 21(7): 70209-070209.