A Mathematical Study of Barcelona Metro Network
暂无分享,去创建一个
Irene Mariñas-Collado | Elisa Frutos Bernal | Maria Teresa Santos Martin | Angel Martín del Rey | Roberto Casado Vara | Ana Belen Gil-González | A. Gil-González | Á. Martín del Rey | I. Mariñas-Collado | E. Frutos Bernal | R. Casado Vara
[1] B. Russo,et al. Flood Risk Assessment in an Underground Railway System under the Impact of Climate Change—A Case Study of the Barcelona Metro , 2020, Sustainability.
[2] Shaopei Chen,et al. Evolution and Evaluation of the Guangzhou Metro Network Topology Based on an Integration of Complex Network Analysis and GIS , 2020 .
[3] Ricardo Lüders,et al. A reduced model for complex network analysis of public transportation systems , 2021 .
[4] C. Stam,et al. The correlation of metrics in complex networks with applications in functional brain networks , 2011 .
[5] H. Sohn,et al. Ridership patterns at subway stations of Seoul capital area and characteristics of station influence area , 2017 .
[6] Jorge Cadima,et al. Principal component analysis: a review and recent developments , 2016, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[7] Wei Yu,et al. Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method , 2020 .
[8] Siuming Lo,et al. Aggregated Metro Trip Patterns in Urban Areas of Hong Kong: Evidence from Automatic Fare Collection Records , 2015 .
[9] S. C. Johnson. Hierarchical clustering schemes , 1967, Psychometrika.
[10] Chuan Ding,et al. How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds , 2019, Journal of Transport Geography.
[11] H. Edelsbrunner,et al. Efficient algorithms for agglomerative hierarchical clustering methods , 1984 .
[12] Cheng Zhou,et al. Quantifying the evolution of settlement risk for surrounding environments in underground construction via complex network analysis , 2020 .
[13] V. Sivakumar,et al. Application of k-means and hierarchical clustering techniques for analysis of air pollution: A review (1980–2019) , 2020 .
[14] Dazhi Sun,et al. Smart Card Data Mining of Public Transport Destination: A Literature Review , 2018, Inf..
[15] Albert-László Barabási,et al. Understanding individual human mobility patterns , 2008, Nature.
[16] Sybil Derrible,et al. The complexity and robustness of metro networks , 2010 .
[17] Chen Jun,et al. Estimating Smart Card Commuters Origin-Destination Distribution Based on APTS Data , 2013 .
[18] Etienne Côme,et al. Analyzing year-to-year changes in public transport passenger behaviour using smart card data , 2017 .
[19] Cynthia Chen,et al. Diurnal Pattern of Transit Ridership: Case Study of New York City Subway System , 2009 .
[20] Roger K. Blashfield,et al. Mixture model tests of cluster analysis: Accuracy of four agglomerative hierarchical methods. , 1976 .
[21] Soledad Moreno-Pulido,et al. Temporal evolution of multifractality in the Madrid Metro subway network , 2020 .
[22] Á. Martín del Rey,et al. Study of the Structural and Robustness Characteristics of Madrid Metro Network , 2019, Sustainability.
[23] Qing Cai,et al. A Smart Path Recommendation Method for Metro Systems With Passenger Preferences , 2020, IEEE Access.
[24] Fionn Murtagh,et al. Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? , 2011, Journal of Classification.
[25] Oded Cats,et al. Topological evolution of a metropolitan rail transport network: The case of Stockholm , 2017 .
[26] Mauricio Barahona,et al. Spectral Measure of Structural Robustness in Complex Networks , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[27] Á. Martín del Rey,et al. Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective , 2020 .
[28] J. Wareham,et al. A Smart City Initiative: the Case of Barcelona , 2012, Journal of the Knowledge Economy.
[29] Shuliang Wang,et al. Networked analysis of the Shanghai subway network, in China , 2011 .
[30] Matthew G. Karlaftis,et al. Sustainable urban transit network design , 2015 .
[31] Wenjing Wang,et al. A Network-Based Model of Passenger Transfer Flow between Bus and Metro: An Application to the Public Transport System of Beijing , 2020 .
[32] Yuanyuan Wang,et al. Measure Vulnerability of Metro Network Under Cascading Failure , 2021, IEEE Access.
[33] Meng Yangyang,et al. Exploring node importance evolution of weighted complex networks in urban rail transit , 2020 .
[34] Marta C. González,et al. Origin-destination trips by purpose and time of day inferred from mobile phone data , 2015 .
[35] Catherine Morency,et al. Smart card data use in public transit: A literature review , 2011 .
[36] R. Mojena,et al. Hierarchical Grouping Methods and Stopping Rules: An Evaluation , 1977, Comput. J..
[37] Ying Lu,et al. Toward a Stakeholder Perspective on Safety Risk Factors of Metro Construction: A Social Network Analysis , 2020, Complex..
[38] Peng Gao,et al. Predicting Station-Level Short-Term Passenger Flow in a Citywide Metro Network Using Spatiotemporal Graph Convolutional Neural Networks , 2019, ISPRS Int. J. Geo Inf..
[39] Jun-Ho Huh,et al. Understanding Edge Computing: Engineering Evolution With Artificial Intelligence , 2019, IEEE Access.
[40] J. H. Ward. Hierarchical Grouping to Optimize an Objective Function , 1963 .
[41] Ahmad Tavassoli,et al. Public transport trip purpose inference using smart card fare data , 2018 .
[42] Jianwei Wang,et al. Research on Bus and Metro Transfer From Perspective of Hypernetwork—A Case Study of Xi’an, China (December 2020) , 2020, IEEE Access.
[43] Haris N. Koutsopoulos,et al. Inferring patterns in the multi-week activity sequences of public transport users , 2016 .
[44] Robert E. Kooij,et al. Multi-criteria robustness analysis of metro networks , 2017 .
[45] Athman Bouguettaya,et al. Efficient agglomerative hierarchical clustering , 2015, Expert Syst. Appl..
[46] Massimo Marchiori,et al. Is the Boston subway a small-world network? , 2002 .
[47] Ke Niu,et al. An Evaluation Method for Emergency Procedures in Automatic Metro Based on Complexity , 2021, IEEE Transactions on Intelligent Transportation Systems.
[48] Jianhua Zhang,et al. Networked characteristics of the urban rail transit networks , 2013 .
[49] Michel Verleysen,et al. Clustering Smart Card Data for Urban Mobility Analysis , 2017, IEEE Transactions on Intelligent Transportation Systems.