A method for identifying urban hotspots based on mobile signaling data

Abstract

The invention provides a city hot spot identification method based on mobile signaling data. The method comprises the following steps: (1) identifying a residing point according to residing duration of a user, and calculating contribution degree of a permanently residing user to a hot spot area; (2) from the number of residing people, judging an active honeycomb according to the value of the number of residing people; (3) performing similarity measurement for all the identified active honeycombs, and clustering based on a density algorithm to mine the hot spot areas of a city; (4) obtaining POIs data of each hot spot area; (5) performing theme setting for the hot spot areas according to the type of the POIs contained in each hot spot area. In the method provided by the invention, the existing mobile network information is used fully, residing point judgment, a permanently residing user attenuation factor and others are introduced for identifying distribution of the city hot spots and calibrating function types thereof, and a certain reference value is provided for going out, traveling and others of people.

Description

technical field [0001] The invention relates to a method for judging urban hotspots based on mobile signaling data. The distribution demand information of hotspot areas is excavated from existing mobile network information and the function type of the judged hotspots is calibrated, which can be used for people's travel, tourism and Provide services such as urban planning, which belongs to the technical field of traffic management and urban planning. Background technique [0002] With the rapid development of society, people's requirements for the quality of life are getting higher and higher. Judging urban hotspot areas and demarcating functional types according to the characteristics of urban population aggregation will help people live more conveniently and comfortably in modern urban planning. It is of great significance to carry out targeted and guided crowd evacuation and avoid traffic congestion. [0003] Traditional identification methods are mainly based on the Glob...

AI Technical Summary

Problems solved by technology

The present invention considers that in actual research and application, data must be obtained through equipment equipped with GPS, which causes problems such as high cost and large investment in equipment. Cause signal loss, resulting in data loss and many other problems

Therefore, it is no longer the best choice to continue to use GPS data to mine hotspots in cities; at the same time, the traditional key technology for judging hotspots, that is, the identification of resident points, does not take into account the resident users such as the user's residence or work place. The impact of the residence point on its clustering results

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