Scenic area passenger flow prediction method and device, server and storage medium

Abstract

The embodiment of the invention relates to the technical field of networks, and discloses a scenic spot passenger flow prediction method and device, a server and a storage medium. The scenic spot passenger flow prediction method provided by the invention comprises the steps of acquiring real-time passenger flow data in a preset geographic range wherein the real-time passenger flow data is passenger flow data in a first preset time period before the current moment; judging whether a prediction day belongs to holidays or not; if judging that the prediction day belongs to the holiday, determining the passenger flow prediction value of the to-be-tested scenic area in the prediction day according to the real-time passenger flow data and the holiday prediction model; and if judging that the prediction day belongs to a non-holiday, determining a passenger flow prediction value of the to-be-tested scenic area in the prediction day according to the real-time passenger flow data and a non-holiday prediction model. According to the embodiment, the passenger flow volume of a scenic area to be detected can be accurately predicted.

Description

technical field [0001] The embodiments of the present invention relate to the field of network technologies, and in particular to a method, device, server and storage medium for predicting passenger flow in a scenic spot. Background technique [0002] With the continuous development of social economy and the gradual improvement of people's quality of life, more and more people like to travel, which makes the tourism industry in various regions of our country have been greatly developed. Now the tourism industry has become one of the most important economic industries. The prosperity and development of the tourism industry undoubtedly has higher requirements for various scenic spots. For the increasingly prosperous and developing tourism industry, it is necessary to accurately predict the passenger flow of the scenic spots. It can help the relevant departments of the scenic spot to make scientific and reasonable planning and decision-making in advance, optimize resource manag...

AI Technical Summary

Problems solved by technology

[0003] The inventors have found that there are at least the following problems in the prior art: At present, when predicting the passenger flow of a scenic spot, the passenger flow of the scenic spot collected is generally processed, for example, the historical passenger flow of the scenic spot is calculated based on a linear regression algorithm. However, the actual passenger flow of the scenic spot is nonlinear, and the actual passenger flow of the scenic spot varies greatly, resulting in large fluctuations in the predicted passenger flow of the scenic spot, which is very inaccurate

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