1 |
YUAN Y H, RAUBAL M. Extracting dynamic urban mobility patterns from mobile phone data[C]//Geographic Information Science, GIS cience 2012.Berlin, Heidelberg :Springer,2012:354-367.
doi: 10.1007/978-3-642-33024-7_26
|
2 |
WANG Y H, ALMEIDA CORREIA G H D, ROMPH E D, et al. Using metro smart card data to model location choice of after-work activities: an application to Shanghai [J]. Journal of Transport Geography, 2017, 63:40-47.
doi: 10.1016/j.jtrangeo.2017.06.010
|
3 |
FENG T, TIMMERMANS H J P. Transportation mode recognition using GPS and accelerometer data[J]. Transportation Research Part C, 2013, 37 : 118-130.
doi: 10.1016/j.trc.2013.09.014
|
4 |
MA X L, WU Y J, WANG Y H, et al. Mining smart card data for transit riders′ travel patterns[J]. Transportation Research Part C: Emerging Technologies, 2013, 36: 1-12.
doi: 10.1016/j.trc.2013.07.010
|
5 |
SUN L J, AXHAUSEN K W, LEE D H, et al. Understanding metropolitan patterns of daily encounters[J]. Proceedings of the National Academy of Sciences of the United States of America, 2013, 110(34): 13774-13779.
doi: 10.1073/pnas.1306440110
|
6 |
NI M, HE Q, GAO J. Forecasting the subway passenger flow under event occurrences with social media[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(6): 1623-1632.
doi: 10.1109/TITS.2016.2611644
|
7 |
王莹, 韩宝明, 张琦, 等. 基于SARIMA模型的北京地铁进站客流量预测[J]. 交通运输系统工程与信息, 2015, 15(6): 205-211.
doi: 10.16097/j.cnki.1009-6744.2015.06.031
|
8 |
刘洋. 城市轨道交通线网客流OD动态估计[D]. 南京: 东南大学, 2017.
|
9 |
姚向明, 赵鹏, 禹丹丹. 城市轨道交通网络短时客流OD估计模型[J]. 交通运输系统工程与信息, 2015, 15(2): 149-155.
doi: 10.16097/j.cnki.1009-6744.2015.02.023
|
10 |
刘钊, 杜威, 闫冬梅, 等. 基于K近邻算法和支持向量回归组合的短时交通流预测[J]. 公路交通科技, 2017, 34(5): 122-128.
doi: 10.3969/j.issn.1002-0268.2017.05.017
|
11 |
TOQUE F, COME E, EL MAHRSI M K, et al. Forecasting dynamic public transport Origin-Destination matrices with long-short term Memory recurrent neural networks[C]//2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC). Rio de Janeiro, Brazil:IEEE, 2016: 1071-1076.
doi: 10.1109/ITSC.2016.7795689
|
12 |
JEONG Y S, BYON Y J, CASTRO-NETO M M, et al. Supervised weighting-online learning algorithm for short-term traffic flow prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(4): 1700-1707.
doi: 10.1109/TITS.2013.2267735
|
13 |
ZHU J Z, CAO J X, ZHU Y. Traffic volume forecasting based on radial basis function neural network with the consideration of traffic flows at the adjacent intersections[J]. Transportation Research Part C: Emerging Technologies, 2014, 47: 139-154.
doi: 10.1016/j.trc.2014.06.011
|
14 |
蔡昌俊, 姚恩建, 张永生, 等. 基于AFC数据的城轨站间客流量分布预测[J]. 中国铁道科学, 2015, 36(1): 126-132.
doi: 10.3969/j.issn.1001-4632.2015.01.18
|
15 |
PNEVMATIKOU A M, KARLAFTIS M G, KEPAPTSOGLOU K. Metro service disruptions: how do people choose to travel?[J].Transportation, 2015, 42(6): 933-949.
doi: 10.1007/s11116-015-9656-4
|
16 |
刘莎莎, 姚恩建, 李斌斌, 等. 基于行为分析的突发事件下城轨站间客流分布预测[J]. 铁道学报, 2018, 40(9): 22-29.
doi: 10.3969/j.issn.1001-8360.2018.09.004
|
17 |
蒋熙, 贾飞凡, 冯佳平. 基于AFC数据的城轨路网客流OD在线动态估计[J]. 交通运输系统工程与信息, 2018, 18(5): 129-135.
doi: 10.16097/j.cnki.1009-6744.2018.05.019
|
18 |
许胜博. 基于AFC数据的地铁乘客出行目的地实时预测[J]. 交通运输工程与信息学报, 2019, 17(2): 81-90.
|
19 |
杜豫川, 陈赣浙, 周小鹏, 等. 基于贝叶斯估计的OD预测方法研究[C]//中国智能交通协会,2014第九届中国智能交通年会论文集. 广州:电子工业出版社, 2014: 240-245.
|