DocumentCode :
2838306
Title :
Golden Week Tourist Flow Forecasting Based on Neural Network
Author :
Wu, Kailiang ; Dai, Bin
Author_Institution :
Zhejiang Univ., Hangzhou
fYear :
2006
fDate :
15-17 Dec. 2006
Firstpage :
2866
Lastpage :
2871
Abstract :
Golden week is a collection of national holidays within seven days. Accurate forecast of tourist flow will boost the business of tourism and optimize the allocation of resources. In this paper, taking Chinese golden week as a case study, we implement a forecasting procedure based on a hybrid model using Kalman filter and neural network. The result of this technique is evaluated and compared with other common forecasting models. We conclude that the hybrid model is effective and outperforms the other methods.
Keywords :
Kalman filters; forecasting theory; neural nets; social sciences computing; Chinese golden week; Kalman filter; national holidays; neural network; tourist flow forecasting; Airports; Artificial neural networks; Autoregressive processes; Boosting; Fluctuations; Neural networks; Partial response channels; Predictive models; Resource management; Weather forecasting; Golden Week; Kalman Filter; Neural Network; Tourist Flow Forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
Conference_Location :
Mumbai
Print_ISBN :
1-4244-0726-5
Electronic_ISBN :
1-4244-0726-5
Type :
conf
DOI :
10.1109/ICIT.2006.372637
Filename :
4237959
Link To Document :
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