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http://dx.doi.org/10.7471/ikeee.2017.21.1.13

Search Trend's Effects On Forecasting the Number of Outbound Passengers of the Incheon Airport  

Shin, Euiseob (Dept. of Electronic Eng., Soonchunhyang Univ.)
Yang, Dong-Heon (R&D Center, Incheon International Airport Corp.)
Sohn, Sei Chang (R&D Center, Incheon International Airport Corp.)
Huh, Moonhaeng (Dept. of Digital Media, Anyang Univ.)
Baek, Seokchul (Dept. of Digital Media, Anyang Univ.)
Publication Information
Journal of IKEEE / v.21, no.1, 2017 , pp. 13-23 More about this Journal
Abstract
Short-term prediction of the number of passengers at the airport is very essential for the efficient and stable operation of the airport. Here, to forecast the immigration of Incheon International Airport, we perform the predictive modeling of Korean and Chinese outbound travelers comprising most of immigration. We conduct the Granger Causality test between the number of outbound travelers and related search trend data to confirm the correlation. It is found that the forecasting with both "outbound travelers" and "search term trends" data outperforms the one only with "outbound travelers" data. This is because search activities are done before doing something and this study confirms that search trend data inherently possess the potential for prediction.
Keywords
Big Data; Search Trend; Forecast Modelling; Linear Regression; Neural Network;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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