In the process of studying the number of tourist arrivals of each moment on every day, one of the key findings is a very good statistical regularity about tourist total arrivals. There exists high similarity among different scales of tourist arrivals, including the nearly same change trend. And on this basis this paper puts forward a new method of modeling and forecasting real-time tourist arrivals of each moment on every day. The forecasting process of the new proposed model is innovative. We consider the scales of tourist arrivals mainly, and model using hierarchical cluster and Gaussian fitting algorithm according to the different scales of tourist arrivals, thus predict real-time arrivals of the future a scale (the overall size of the known) through the existing scales. Finally take Jiuzhai Valley as an example to analysis, and experimental results show that the forecast method is effective.
Digital Object Identifier (DOI)
Yao, Lifei; Ma, Ruimin; Jin, Maozhu; Ge, Peng; and Ren, Peiyu
"Forecasting Real-Time Tourist Arrivals using Hierarchical Cluster and Gaussian Fitting Algorithm: A Case Study of Jiuzhai Valley,"
Applied Mathematics & Information Sciences: Vol. 08:
3, Article 60.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss3/60