Journal of Guangdong University of Technology ›› 2022, Vol. 39 ›› Issue (03): 1-7.doi: 10.12052/gdutxb.210158

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Application of GeoHash and KNN in the Optimization Selection of Shared Bicycle Stops

Wang Xiao-xia, Ouyang Lu, Zheng Shi-qi, Hu San-gen, Han Shuang   

  1. School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2021-10-24 Online:2022-05-10 Published:2022-05-19

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Abstract: To deal with the problems of time-space imbalance between supply and demand of shared bicycle stops, obvious tidal effect and low level of optimization selection, by combining region coding with classification learning method, an optimal selection method of shared bicycle stops is proposed based on GeoHash and KNN. Firstly, based on the analysis of the existing shared bicycle parking problem, the spatial distribution of parking points is obtained by using the region coding segmentation of GeoHash algorithm. Then, under the double constraints of the number of stops and the bicycles that can be accommodated, the KNN clustering algorithm is used for secondary division to complete the optimal selection of shared bicycle stops. Finally, a comprehensive evaluation is carried out based on the shared bicycle data of Siming District and Huli District in Xiamen. The result shows that this method is reasonable, which can provide a useful reference for alleviating the tide phenomenon of shared bicycle stops.

Key words: shared bicycle, optimization of stops, GeoHash encoding, KNN algorithm, tide phenomenon

CLC Number: 

  • U121
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