Scenic area passenger flow real-time prediction method based on tourist time-space behavior pattern mining

The invention provides a scenic spot passenger flow real-time prediction method based on tourist time-space behavior pattern mining. The scenic spot passenger flow real-time prediction method comprises the following steps: S1, real-time collection of big data: carrying out real-time collection on basic information, time-space behavior data, traffic condition data, meteorological data and destination festival data of tourists; s2, mining a space-time behavior mode of tourists and constructing a space reachability model between scenic spots; s3, predicting the passenger flow quantity of each scenic spot in the next prediction period by using the model constructed in the step S2 according to the spatial and temporal distribution of tourists in each scenic spot at the current moment of the destination, tourist movement directivity information and traffic condition data; and S4, performing iterative updating on the model constructed in the step S2 according to tourist spatio-temporal data generated in real time in