| 基于信息传递效率的地铁网络小世界特性评价 |
| 王志如1, 苏国锋1, 梁作论2 |
| 1. 清华大学 公共安全研究院, 北京 100084; 2. 中国电子集团 南京十四所, 南京 210031 |
| Information transfer efficiency based small-world assessment methodology for metro networks |
| WANG Zhiru1, SU Guofeng1, LIANG Zuolun2 |
| 1. Institution of Public Safety, Tsinghua University, Beijing 100084, China; 2. The 14th Institution of Nanjing, Electronic Technology Group Corporation, Nanjing 210031, China |
摘要:
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| 摘要为了差异化直接相邻和间接相邻的车站对信息传递效率的影响,该文建立了基于信息传递效率的聚类系数模型,构建了地铁网络小世界特性评价方法。通过对全球52个城市的地铁网络样本的小世界特征值计算,得到基于信息传递效率的聚类系数算法的聚类系数值在0.195~0.407之间,平均值为0.29,虽然小于以线路为演化单位的公共交通网络中P空间(Space-of-Stops)下的聚类系数值,仍然远大于相同规模的随机网络聚类系数值(0.01~0.16,平均值为0.06)。故认为基于信息传递效率的聚类系数算法能够更加严格地评价物理网络是否具有小世界特性。在此方法下,52个样本城市地铁网络仍具有小世界特性。 | |||
| 关键词 ：地铁网络,小世界,聚类系数,效率 | |||
| Abstract：This study presents an improved algorithm for the clustering coefficient in a metro network model. The algorithm is based on the information transfer efficiency that considers the differences between the directly and indirectly connected origin-to-destination stations. The algorithm was evaluated using 52 metro networks in the world. The information transfer efficiency based clustering coefficients for the 52 metro networks are between 0.195 and 0.407 (average 0.29), which is lower than the value given by P-Space (Space-of-Stops), but still considerably higher than the values for random networks (0.01 to 0.16, the average is 0.06) with the same size. Therefore, metro networks are small-world networks, although with a stricter evaluation model. | |||
| Key words：metro networksmall-worldclustering coefficientsefficiency | |||
| 收稿日期: 2015-01-15 出版日期: 2016-05-09 | |||
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| 通讯作者:苏国锋,研究员。E-mail:sugf@mail.tsinghua.edu.cnE-mail: sugf@mail.tsinghua.edu.cn | |||
| 引用本文: |
| 王志如, 苏国锋, 梁作论. 基于信息传递效率的地铁网络小世界特性评价[J]. 清华大学学报（自然科学版）, 2016, 56(4): 411-416. WANG Zhiru, SU Guofeng, LIANG Zuolun. Information transfer efficiency based small-world assessment methodology for metro networks. Journal of Tsinghua University(Science and Technology), 2016, 56(4): 411-416. |
| 链接本文: |
| http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2016.24.012或 http://jst.tsinghuajournals.com/CN/Y2016/V56/I4/411 |
图表:
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| 图１ 示例地铁网络及其不同分析模型 |
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| 表１ 公共交通网络的聚类系数值 |
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| 图２ 基于信息传递效率的聚类系数算法下的示例地铁网络模型 |
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| 图4 地铁网络聚类系数值与相同规模随机网络聚类系数值比较 |
参考文献:
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