计算机科学 ›› 2018, Vol. 45 ›› Issue (8): 125-130.doi: 10.11896/j.issn.1002-137X.2018.08.022
孔繁钰1, 周愉峰2, 李献忠3
KONG Fan-yu1, ZHOU Yu-feng2, LI Xian-zhong3
摘要: 针对城市公交网络中换乘网络的整体性能分析问题,提出一种基于复杂网络理论的分析方法。首先,基于图论思想,将公交网络建模成由Space-P方法表示的公交换乘网络拓扑模型;然后,统计分析了公交换乘网络的度分布、平均最短路径长度、聚类系数、紧密中心性和介数中心性等特性。以北京市的公交网络为例进行了相关分析,从宏观角度说明北京公交网络具有小世界网络特点,市民出行需要换乘的概率较大,但换乘较为便捷;同时,给出了相关站点的具体地理信息,为公交规划部门优化公交网络提供了参考。
中图分类号:
[1]LIANG Y,MA Q S,XU P.Sneak circuit partition analysis me-thod based on graph theory [J].Journal of Beijing University of Aeronautics and Astronautics,2014,40(1):115-119.(in Chinese)梁因,马齐爽,徐萍.基于图论的潜通路分块分析方法[J].北京航空航天大学学报,2014,40(1):115-119. [2]CHAO Y C,JI Z J,WANG Y W,et al.Necessary and sufficient conditions for the controllability of complex networks with path topology[J].CAAI Transactions on Intelligent Systems,2015,10(4):577-582.(in Chinese)晁永翠,纪志坚,王耀威,等.复杂网络在路形拓扑结构下可控的充要条件[J].智能系统学报,2015,10(4):577-582. [3]OSTILLI M,FERREIRA A L,MENDES J F.Critical behavior and correlations on scale-free small-world networks:application to network design[J].Physical Review E Statistical Nonlinear &Soft Matter Physics,2011,83(1):149-155. [4]ZHANG Y,ZHANG Q,QIAO J.Analysis of Guangzhou metro network based on L-space and P-space using complex network[C]∥International Conference on Geoinformatics.IEEE:Piscataway,NJ,2014:1-6. [5]XU P P,SHAO C F.A RLP Modeling and Complexity Analysis on Urban Transit Network[J].Journal of Wuhan University of Technology(Transportation Science & Engineering),2016,40(2):321-325.(in Chinese)徐佩佩,邵春福.城市公共交通网络RLP建模及复杂性分析[J].武汉理工大学学报(交通科学与工程版),2016,40(2):321-325. [6]WANG T,CHEN J.Space P-Based Urban Public Transit Complex Network Characteristics of Different-Scale Cities[C]∥Cota International Conference of Transportation Professionals.IEEE:Piscataway,NJ,2016:913-923. [7]WATTS D J,STROGATZ S H.collective dynamics of ‘small world’ networks[J].Nature,1998,393(5):440-442. [8]BARABASI A L,ALBERT R.Emergence of Scaling in Random Networks[J].Science,1999,286(9):509-512. [9]ZHANG H,ZHAO P,GAO J,et al.The Analysis of the Properties of Bus Network Topology in Beijing Basing on Complex Networks[J].Mathematical Problems in Engineering,2012,10(1):127-148. [10]ZHANG N,MAO G.A Multilevel Simplification Algorithm forComputing the Average Shortest-Path Length of Scale-Free Complex Network[J].Journal of Applied Mathematics,2014,26(4):1-6. [11]LIU H,ZHOU G G,FU P H.Local Evolving Model Research of Layered Supply Chains Complex Networks[J].Computer Scien-ce,2013,40(2):270-273.(in Chinese)柳虹,周根贵,傅培华.分层供应链复杂网络局部演化模型研究[J].计算机科学,2013,40(2):270-273. [12]XU Q,ZU Z H,XU Z J ,et al.Space P-Based Empirical Re-search on Public Transport Complex Networks in 330 Cities of China[J].Journal of Transportation Systems Engineering & Information Technology,2013,13(1):193-198. [13]WEHMUTH K,ZIVIANI A.Distributed assessment of thecloseness centrality ranking in complex networks[C]∥The Workshop on Simplifying Complex Networks for Practitioners.ACM:New York,NY,2012:43-48. [14]TIAN Y,LIU Z G.Detecting Most Influential Nodes in Complex Networks by KSN Algorithm [J].Computer Science,2015,42(11A):296-300.(in Chinese)田艳,刘祖根.利用KSN算法发现网络中有影响力的结点[J].计算机科学,2015,42(11A):296-300. [15]HU P,FAN W L.Invulnerability of urban transit network under different attack modes[J].Application Research of Computers,2014,31(11):3385-3391.(in Chinese)胡萍,范文礼.不同攻击模式下城市公交网络抗毁性分析[J].计算机应用研究,2014,31(11):3385-3391. [16]SUN D H,FU Q S,LI Y F.Forecasting of Public Traffic Passenger Volume Based on Quantum Neural Network.Journal of Chongqing University of Technology(Natural Science),2011,25(2):96-99,111.(in Chinese)孙棣华,付青松,李永福.基于量子神经网络的公交客运量预测[J].重庆理工大学学报(自然科学),2011,25(2):96-99,111. |
[1] | 郑文萍, 刘美麟, 杨贵. 一种基于节点稳定性和邻域相似性的社区发现算法 Community Detection Algorithm Based on Node Stability and Neighbor Similarity 计算机科学, 2022, 49(9): 83-91. https://doi.org/10.11896/jsjkx.220400146 |
[2] | 杨波, 李远彪. 数据科学与大数据技术课程体系的复杂网络分析 Complex Network Analysis on Curriculum System of Data Science and Big Data Technology 计算机科学, 2022, 49(6A): 680-685. https://doi.org/10.11896/jsjkx.210800123 |
[3] | 何茜, 贺可太, 王金山, 林绅文, 杨菁林, 冯玉超. 比特币实体交易模式分析 Analysis of Bitcoin Entity Transaction Patterns 计算机科学, 2022, 49(6A): 502-507. https://doi.org/10.11896/jsjkx.210600178 |
[4] | 王本钰, 顾益军, 彭舒凡, 郑棣文. 融合动态距离和随机竞争学习的社区发现算法 Community Detection Algorithm Based on Dynamic Distance and Stochastic Competitive Learning 计算机科学, 2022, 49(5): 170-178. https://doi.org/10.11896/jsjkx.210300206 |
[5] | 陈世聪, 袁得嵛, 黄淑华, 杨明. 基于结构深度网络嵌入模型的节点标签分类算法 Node Label Classification Algorithm Based on Structural Depth Network Embedding Model 计算机科学, 2022, 49(3): 105-112. https://doi.org/10.11896/jsjkx.201000177 |
[6] | 赵学磊, 季新生, 刘树新, 李英乐, 李海涛. 基于路径连接强度的有向网络链路预测方法 Link Prediction Method for Directed Networks Based on Path Connection Strength 计算机科学, 2022, 49(2): 216-222. https://doi.org/10.11896/jsjkx.210100107 |
[7] | 李家文, 郭炳晖, 杨小博, 郑志明. 基于信息传播的致病基因识别研究 Disease Genes Recognition Based on Information Propagation 计算机科学, 2022, 49(1): 264-270. https://doi.org/10.11896/jsjkx.201100129 |
[8] | 穆俊芳, 郑文萍, 王杰, 梁吉业. 基于重连机制的复杂网络鲁棒性分析 Robustness Analysis of Complex Network Based on Rewiring Mechanism 计算机科学, 2021, 48(7): 130-136. https://doi.org/10.11896/jsjkx.201000108 |
[9] | 胡军, 王雨桐, 何欣蔚, 武晖栋, 李慧嘉. 基于复杂网络的全球航空网络结构分析与应用 Analysis and Application of Global Aviation Network Structure Based on Complex Network 计算机科学, 2021, 48(6A): 321-325. https://doi.org/10.11896/jsjkx.200900112 |
[10] | 王学光, 张爱新, 窦炳琳. 复杂网络上的非线性负载容量模型 Non-linear Load Capacity Model of Complex Networks 计算机科学, 2021, 48(6): 282-287. https://doi.org/10.11896/jsjkx.200700040 |
[11] | 马媛媛, 韩华, 瞿倩倩. 基于节点亲密度的重要性评估算法 Importance Evaluation Algorithm Based on Node Intimate Degree 计算机科学, 2021, 48(5): 140-146. https://doi.org/10.11896/jsjkx.200300184 |
[12] | 殷子樵, 郭炳晖, 马双鸽, 米志龙, 孙怡帆, 郑志明. 群智体系网络结构的自治调节:从生物调控网络结构谈起 Autonomous Structural Adjustment of Crowd Intelligence Network: Begin from Structure of Biological Regulatory Network 计算机科学, 2021, 48(5): 184-189. https://doi.org/10.11896/jsjkx.210200161 |
[13] | 刘胜久, 李天瑞, 谢鹏, 刘佳. 带权图的多重分形度量 Measure for Multi-fractals of Weighted Graphs 计算机科学, 2021, 48(3): 136-143. https://doi.org/10.11896/jsjkx.200700159 |
[14] | 龚追飞, 魏传佳. 基于改进AdaBoost算法的复杂网络链路预测 Link Prediction of Complex Network Based on Improved AdaBoost Algorithm 计算机科学, 2021, 48(3): 158-162. https://doi.org/10.11896/jsjkx.200600075 |
[15] | 龚追飞, 魏传佳. 基于拓扑相似和XGBoost的复杂网络链路预测方法 Complex Network Link Prediction Method Based on Topology Similarity and XGBoost 计算机科学, 2021, 48(12): 226-230. https://doi.org/10.11896/jsjkx.200800026 |
|