Travel spot passenger flow dynamic prediction method

Abstract

The invention discloses a travel spot passenger flow dynamic prediction method; the travel spot passenger flow dynamic prediction method combines a statistics method with a nerve network, considers various factor influences on the traveling, and combines a trend extrapolation method, a monthly index method and a fluctuation coefficient method in the statistics with a BPNN; the travel spot passenger flow dynamic prediction method considers various factors affecting the travelling, uses the monthly index to divide history visitors into small scale data, uses the BP to fully study, and finally uses the fluctuation coefficient to dynamically predict the travel spot passenger flow according to the holiday real conditions, thus providing large conveniences for a travel spot manager, providing guidance effect for travelers, and dynamically predicting the holiday passenger flows according to the future holiday real conditions.

Description

【Technical field】

[0001] The invention belongs to the field of passenger flow prediction of tourist attractions, relates to technologies such as statistics and neural networks, and specifically relates to a method for dynamically predicting passenger flow of tourist attractions. 【Background technique】

[0002] At present, the tourism industry is developing rapidly. Every weekend and holiday, the passenger flow of tourist attractions increases sharply. The passenger flow exceeding the load of scenic spots will not only destroy the balance of scenic spots, but also bring a huge threat to the management of tourism management departments. In order to effectively control the passenger flow of tourist attractions and maintain the ecological balance of tourist attractions, accurate and effective forecasting of tourist passenger flow has become a hot and difficult issue in tourism research today.

[0003] At present, there are many methods for tourist passenger flow forecasting, wh...

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