Research on prediction of tourists' quantity in Jiuzhaigou Valley scenic based on ABR@G integration model
by Zhixue Liao; Maozhu Jin; Yuyan Luo; Peiyu Ren; Huafeng Gao
International Journal of Environment and Pollution (IJEP), Vol. 51, No. 3/4, 2013

Abstract: As the uncertain changes of tourists' quantity have challenged scenic management, which affects the environmental pollution, many researches confirm that forecasting, which is the foundation of the tourists' management can provide guarantee of effective environment protection. Because the changes of tourists' quantity with complex characteristics of the linear and non-linear are mutually integrated, prediction accuracy of a single model alone or traditional combination model using the simple linear combination method is poor. This paper proposes the AI techniques integration method (the special combination method) - GMDH which can improve forecasting accuracy of that kind of data. The ABR@G model which is applied to predict that kind of data is built through integrating the seasonal ARMA model, neural network model and revised ARIMA model with the AI techniques integration method. Finally, Jiuzhaigou Valley scenic is taken as the subject of the research to do empirical analysis which proves that the model in predicting the quantity of tourists is valid.

Online publication date: Fri, 28-Feb-2014

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