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1. 陈学武 , 陈学武 , 戴霄,陈茜 . 公交 IC 卡信息采集、分析与应用研究 [J]. 土木工程学报, 2004 , 37 ( 2 ): 105 ~ 110.
2. 陈学武 , 葛宏伟 , 王炜,城市公交优先发展的对策研究 [J] ,现代城市研究, 2004 ( 1 ): 34 ~ 36
3. 陈学武 , 李文勇,主动式公交线网规划模式研究与实施 [J] ,武汉理工大学学报 ( 交通科学与工程版 ) , 2006 , 30 ( 1 ): 9 ~ 12.
4. 陈学武 , 刘飞 , 刘启洲,小城市道路网的合理道路级配模型 [J] ,交通运输工程学报, 2008 , 8(01):102-105.
5. 毕晓萤 , 陈学武 , 李子木 . 基于 L 空间改进的城市快速公交网络特性研究 [J] . 交通运输系统工程与信息 [J] , 2011 , 11(05):173-180.
6. 李海波, 陈学武, 陈峥嵘. 基于公交IC卡和AVL数据的客流OD推导方法 [J]. 交通信息与安全, 2015, 33(06): 33-39+95.
7. 魏明, 陈学武, 孙博. 公交站场选址布局优化模型和算法 [J]. 交通运输系统工程与信息, 2015, 15(04): 113-117.
8. 魏明, 陈学武, 孙博. 配合大站快车的单线公交组合调度模型 [J]. 交通运输系统工程与信息, 2015, 15(02): 169-174+181.
9. 程龙, 陈学武, 杨硕, 王海啸. 基于支持向量机的低收入通勤者出行方式预测 [J]. 武汉理工大学学报(交通科学版与工程版), 2016, 40(4): 619-622.
10. 程龙, 陈学武, 杨硕, 袁明义. 基于市场细分的低收入通勤者公交出行改善对策 [J]. 交通运输系统工程与信息, 2016, 16(03): 8-14.
11. 侯现耀 , 陈学武 , 曾隽 . 公交出行信息条件下出行者通勤出发时间选择影响因素 [J]. 东南大学学报 ( 自然科学版 ),2016,46(04):893-898.
12. 陈学武 , 安萌,中国 TOD 发展模式的再探索 [J]. 交通工程 ,2018, 18 ( 5 )
13. 徐特, 陈学武, 杨敏, 吴静娴. 基于深度学习的城市地面公交客流集散点刷卡客流预测—以常州市为例 [J]. 交通工程, 2018, 18(02): 13-18.
14. 侯现耀, 陈学武. 基于态度的公交出行信息使用市场细分 [J]. 吉林大学学报(工学版), 2018, 48(01): 98-104.
15. 雷达,陈学武,程龙,罗荣根.基于公交刷卡数据的老年乘客与普通成年乘客上车时间差别分析[J].Journal of Southeast University (English Edition),2019,35(01):97-102.
16. 华明壮, 王彤彦, 陈学武, 程龙, 曹锴. 基于刷卡数据的公共自行车交通流特性研究 [J]. 交通工程, 2019, 19: 65-72.
17. 周航, 陈学武. 城市公共交通通勤者活动出行链构建与特征提取方法 [J]. 交通工程, 2022, 22(01): 22-28+34.
18. 周航, 陈学武. 集时空聚类和指标筛选的公共交通通勤者识别 [J]. 交通运输工程与信息学报, 2022, 20(01): 89-97.
19. 成骋, 陈文栋, 马洪生, 刘锡泽, 陈学武. 基于Leiden算法的共享单车活动社区识别方法—南京案例分析 [J]. 交通信息与安全, 2023, 41(02): 103-111+156.
20. 王伊凡, 陈学武. 考虑空间效应的公交站点客流量影响因素分析 [J]. 交通运输系统工程与信息, 2023, 23(06): 153-164.
21. Jiao Q, Wang J, Cheng L, Chen X, et al. Carbon emission reduction effects of heterogeneous car travelers under green travel incentive strategies[J]. Applied Energy , 2024, 379: 124826.
22. Liu X, Chen W, Chen X , et al. Is increasing the frequency an effective measure for the renaissance of inter-city coach? A longitudinal study of the relation between volume and frequency[J]. Travel Behaviour and Society , 2024, 35: 100741.
23. Chen W, Chen X, , et al. Locating new docked bike sharing stations considering demand suitability and spatial accessibility , Travel Behaviour and Society , 2024.
24. Chen W, Chen X, Chen J, Cheng L. What factors influence ridership of station-based bike sharing and free-floating bike sharing at rail transit stations? [J]. International Journal of Sustainable Transportation, 2022, 16(4): 357-373.
25. Hua M, Chen X, Chen J, Cheng L, Lei D. How does dockless bike sharing serve users in Nanjing, China? User surveys vs. trip records [J]. Research in Transportation Business & Management, 2022, 43: 100701.
26. Chen W, Liu X, Chen X, Cheng L, Wang K, Chen J. Exploring year-to-year changes in station-based bike sharing commuter behaviors with smart card data [J]. Travel Behaviour and Society, 2022, 28: 75-89.
27. Chen W, Chen X, Cheng L, Liu X, Chen J. Delineating borders of urban activity zones with free-floating bike sharing spatial interaction network [J]. Journal of Transport Geography, 2022, 104: 103442.
28. Lei D, Chen X, Cheng L, et al. Minimum entropy rate-improved trip-chain method for origin–destination estimation using smart card data. Transportation Research Part C: Emerging Technologies, 2021, 130: 103307.
29. Wang P, Chen X, Zheng Y, et al. Providing real-time bus crowding information for passengers: a novel policy to promote high-frequency transit performance. Transportation Research Part A: Policy and Practice, 2021, 148: 316-329.
30. Chen W, Cheng L, Chen X, et al. Measuring accessibility to health care services for older bus passengers: A finer spatial resolution. Journal of Transport Geography, 2021, 93: 103068.
31. Chen W, Chen X, Chen J, et al. What factors influence ridership of station-based bike sharing and free-floating bike sharing at rail transit stations?. International Journal of Sustainable Transportation, 2022, 16(4): 357-373.
32. Hua M, Chen X, Chen J, et al. How does Dockless bike sharing serve users in Nanjing, China? User surveys vs. trip records. Research in Transportation Business & Management, 2022, 43: 100701.
33. Lei D, Chen X, Cheng L, et al. Inferring temporal motifs for travel pattern analysis using large scale smart card data. Transportation Research Part C: Emerging Technologies, 2020, 120: 102810.
34. Hua M, Chen J, Chen X, et al. Forecasting usage and bike distribution of dockless bike‐sharing using journey data. IET Intelligent Transport Systems, 2020, 14(12): 1647-1656.
35. Wang P, Chen X, Chen J, et al. A two‐stage method for bus passenger load prediction using automatic passenger counting data. IET Intelligent Transport Systems, 2021, 15(2): 248-260.
36. Hua M, Chen X, Zheng S, et al. Estimating the parking demand of free-floating bike sharing: A journey-data-based study of Nanjing, China. Journal of Cleaner Production, 2020, 244: 118764.
37. Cheng L, Chen X, Yang S, et al. Active travel for active ageing in China: The role of built environment. Journal of transport geography, 2019, 76: 142-152.
38. Cheng L, Chen X, Yang S, et al. Structural equation models to analyze activity participation, trip generation, and mode choice of low-income commuters. Transp. Lett. 11, 341–349 (2019). 2019.
39. Cheng L, Chen X, De Vos J, et al. Applying a random forest method approach to model travel mode choice behavior. Travel behaviour and society, 2019, 14: 1-10.
40. Wang P, Chen X, Chen W, et al. Provision of bus real-time information: Turning passengers from being contributors of headway irregularity to controllers. Transportation Research Record, 2018, 2672(8): 143-151.
41. Cheng L, Chen X, Lam W H K, et al. Improving travel quality of low-income commuters in China: demand-side perspective. Transportation Research Record, 2017, 2605(1): 99-108.
42. Cheng L, Chen X, Lam W H K, et al. Public transit market research of low-income commuters using attitude-based market segmentation approach: case study of Fushun, China. Transportation research record, 2017, 2671(1): 10-19.