Multi-granularity urban public bicycle scheduling method and system based on DBScan

Abstract

The invention discloses a multi-granularity urban public bicycle scheduling method and a system based on DBScan. The scheduling method is implemented based on the following clustering method: S110, using a site as a clustering object to draw a k-dist graph of the clustering object; S120, extracting an inflection point of a k-dist graph curve, wherein region radius corresponding to all inflection points form a neighborhood radius value set; and S130, clustering the clustering objects of the corresponding levels by adopting the DBScan method for each neighborhood radius value, obtaining clustersof different levels. According to the clustering result, the multi-granularity urban public bicycle scheduling method and the system based on DBScan respectively obtains the regions formed by all theclusters corresponding to each level that is a scheduling unit. According to the hierarchy from high to low, a city public bicycle scheduling scheme of each level is sequentially formulated. According to the multi-granularity urban public bicycle scheduling method and the system based on DBScan, the problem of poor clustering quality caused by uneven distribution of public bicycle stations can effectively solved, and the invention benefits to improving the clustering quality and furthermore improving the effectiveness of scheduling.

Description

technical field [0001] The invention belongs to the field of urban public bicycle system management, operation maintenance and related applications, in particular to a multi-granularity urban public bicycle scheduling method based on DBScan (Density-Based Spatial Clustering of Applications with Noise, a density-based clustering method with noise) and system. Background technique [0002] Facing the ever-increasing urban traffic problems and deteriorating ecological environment, it has become the consensus of all walks of life to vigorously develop urban public transport. As a green and low-carbon way of travel, public bicycles are becoming more and more popular. However, due to the asymmetry of urban traffic flow and the uncertainty of user demand, public bicycles cannot spontaneously form a relatively balanced distribution among various rental points, and many rental points often appear "no car to borrow" or "no seat The phenomenon of "can be returned" has caused many cit...

AI Technical Summary

Problems solved by technology

[0013] Aiming at the problem that the traditional urban public bicycle station clustering method does not consider the uneven distribution of urban public bicycle stations, the present invention provides a multi-granularity urban public bicycle scheduling method and system based on DBScan

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