Around The Scenic Tourist Space Capacity Prediction

Nowadays, it is getting more severe than ever that some hot tourist destinations are facing a big trouble with increasing jam of tourists. However, the existing forecasting model and algorithm is too simple to effectively predict the overload of tourist carrying capacity, and thus cannot be applied in practice. The goal of this thesis is to propose a method to solve the above problems. In most scenic areas, the flow of tourists normally follows a certain fixed pattern because of their characteristic arrangement on the routes as well as the different level of attraction, which results in the overload of tourists over certain spots. Due to the similarity between the tourist flow and the traffic flow in terms of their dynamic property, viscosity and compressibility, the theory in traffic control and Logit model is utilized to predict the spatial distribution tourist flow with any given scenic area.We have applied both Eviews-based time series analysis and Logistic regression using SPSS on realistically observed data. The result shows that the conventional time-series analysis will produce larger error compared with our proposed method, which has accuracy rate as high as 88.9%.