Finding Key Stations of Hangzhou Public Bicycle System by a Improved K-Means Algorithm

Abstract:

In China, Hangzhou is the first city to set up the Public Bicycle System. Now, the System has been the largest bike- sharing program in the world. The software of Hangzhou Public Bicycle System was developed by our team. There are many and many technology problems in the decision of intelligent dispatch. Among of these problems, determining how to find the key stations to give special care is very important. In this paper, a improved k-means algorithm is used to recognize the key stations of Hangzhou Public Bicycle System. At first, by passing over the two week’s real data, a rent-return database is initialed. Then the algorithm builds minimum spanning tree and splits it to gets k initial cluster centers. The key stations are determined from the rent-return database by the algorithm. Practice examples and comparison with the traditional k-means algorithm are made. The results show that the proposed algorithm is efficient and robust. The research result has been applied in Hangzhou.

• Periodical: Applied Mechanics and Materials (Volumes 209-211)
• Pages: 925-929
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.209-211.925
• Online since: October 2012
• Authors: Hai Tao Xu, Hao Wu, Xu Jian Fang, Wan Jun Zhang
• Keywords: Clustering, Data Mining (DM), K-Means Algorithm, Public Bicycle System

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