Cluster communication terminal track real time anomaly detection method and system based on hybrid grid hierarchical clustering

Abstract

The invention relates to the communication field, and provides a cluster communication terminal track real time anomaly detection method and system based on hybrid grid hierarchical clustering. The method comprises the steps: the step 1: constructing a track based on grids, and determining the size of the optimal grid; the step 2: calculating a Hausdroff distance matrix, utilizing a Hausdroff distance formula to calculate the distance between all the tracks based on the tracks of the grids, and generating a distance matrix of a track set; the step 3: hierarchical clustering, that is, based on the Hausdroff distance matrix of the track set, applying an agglomerate hierarchical clustering algorithm from bottom to top to realize classification of normal and abnormal tracks of a large scale of tracks; and the step 4: anomaly detection method evaluation and feedback: utilizing the above method to perform anomaly track detection on the track set which has a track classification identifier to obtain an anomaly classification result, and evaluating whether a model parameter is reasonable after comparison and making a feedback. The cluster communication terminal track real time anomaly detection method based on hybrid grid hierarchical clustering can realize on-line real time detection of an anomalous event, and can improve the upper layer dispatching efficiency of a cluster communication system.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a method and system for real-time anomaly detection of cluster communication terminal trajectories based on hybrid grid layered clustering. Background technique [0002] With the rapid development of mobile object positioning technologies such as GPS, RFID and wireless sensors, more and more mobile trajectory data are collected and stored in application servers. How to quickly discover effective information from these trajectory data sets has increasingly become a research topic of concern. Therefore, a series of location-based services (LBS) have emerged one after another, such as taxi hailing service, location monitoring of children and the elderly, and location management of important equipment. Obtain the location information (geographic coordinates or geodetic coordinates) of mobile terminal users through the radio communication network (such as GSM network, CDMA net...

AI Technical Summary

Problems solved by technology

The current abnormal trajectory detection method performs well on small-scale trajectory data, but it is very time-consuming when processing massive data. The time complexity of the system becomes larger with the size of the data, which greatly reduces the scheduling efficiency of the cluster communication system.

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