Scene dependence-based illegal tourism path dynamic prediction method

Abstract

The invention discloses a scene dependence-based illegal tourism path dynamic prediction method, which comprises the following steps of step 101, obtaining the urban road network data, POI (Point of Interest) data and police station data, and carrying out preprocessing operation on the data, step 102, constructing a road network undirected graph according to the urban road network data, step 103,constraining the POI (excluding the police office) and the police office on the road network, step 104, calculating the influence of different types of POIs (excluding police offices), road sections and police offices on illegal tourism, step 105, performing dimensionless processing on the index data by adopting a averaging method, step 106, performing road section weight calculation on differentroad sections, and constructing an arc section weight matrix of the road network undirected graph G according to the calculated road section weights, step 107, carrying out dynamic prediction on a known path of the tourist destination, step 108: carrying out dynamic prediction on a path with an unknown tourism end point, and step 109, dynamically updating the path of the tourist in real time.

Description

technical field [0001] The invention relates to the field of spatio-temporal data mining and public security, in particular to a method for dynamic prediction of illegal parade paths based on scene dependence. Background technique [0002] Illegal parade is a sudden group activity that endangers public safety and disrupts social order. Illegal demonstrations are generally non-spontaneous events with a certain organizational structure. Participants in illegal parades generally gather in specific public places within a certain period of time, and carry out a certain scale of crowd movement along the main roads of the city. During the process of parade activities, conflicts are prone to occur, which are destructive to a certain extent and affect normal social life. Practice has proved that the main participants of the illegal parade activities will carry out certain preparations in advance, and under the instigation of the organizers, there will be echoers during the parade p...

AI Technical Summary

Problems solved by technology

[0004] Through the above analysis, it can be found that the existing research methods only carry out risk assessment, early warning and simulation of events based on the internal evolution law of the main body of the procession, and do not fully understand the time-space evolution law of the main body of the illegal procession group event in a specific scene, resulting in the inability to realize the illegal process. Accurate prediction of the full-cycle evolution of parade events, but cannot provide correct decision-making basis for relevant departments

At present, there is still a lack of a dynamic prediction method for illegal parade paths supported by scene dependence

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