发表论文
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A data driven agent-based model that recommends non-pharmaceutical interventions to suppress COVID-19 resurgence in megacities. Journal of the Royal Society Interface[J]. 2021, [5] Yin, Ling, Lin, Nan, Zhao, Zhiyuan. Mining Daily Activity Chains from Large-Scale Mobile Phone Location Data. CITIES[J]. 2021, 109: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809620/.[6] 方志祥, 裴韬, 尹凌. “全球新型冠状病毒肺炎(COVID-19)疫情动态的时空建模与可视化决策分析”专辑导言. 地球信息科学学报. 2021, 23(2): 187-187, http://lib.cqvip.com/Qikan/Article/Detail?id=7104188983.[7] Yang, Xiping, Fang, Zhixiang, Xu, Yang, Yin, Ling, Li, Junyi, Zhao, Zhiyuan. Revealing temporal stay patterns in human mobility using large-scale mobile phone location data. TRANSACTIONS IN GIS[J]. 2021, 25(4): 1927-1948, http://dx.doi.org/10.1111/tgis.12750.[8] Guo, Sihui, Pei, Tao, Xie, Shuyun, Song, Ci, Chen, Jie, Liu, Yaxi, Shu, Hua, Wang, Xi, Yin, Ling. Fractal dimension of job-housing flows: A comparison between Beijing and Shenzhen. CITIES[J]. 2021, 112: http://dx.doi.org/10.1016/j.cities.2021.103120.[9] 吕鸿鑫, 周如意, 尹凌, 梅树江. 深圳市基层应急人员应急知识水平影响因素. 华南预防医学. 2021, 47(1): 97-100, http://lib.cqvip.com/Qikan/Article/Detail?id=7104042835.[10] 张浩, 尹凌, 刘康, 毛亮, 冯圣中, 陈洁, 梅树江. 深圳市快速抑制COVID-19疫情的非药物干预措施效果评估:基于智能体的建模研究. 地球信息科学学报[J]. 2021, 23(11): 1936-1945, http://lib.cqvip.com/Qikan/Article/Detail?id=7106547994.[11] Liu, Kang, Yin, Ling, Lu, Feng, Mou, Naixia. Visualizing and exploring POI configurations of urban regions on POI-type semantic space. CITIES[J]. 2020, 99: http://dx.doi.org/10.1016/j.cities.2020.102610.[12] Zhao, ZeYu, Zhu, YuanZhao, Xu, JingWen, Hu, ShiXiong, Hu, QingQing, Lei, Zhao, Rui, Jia, Liu, XingChun, Wang, Yao, Yang, Meng, Luo, Li, Yu, ShanShan, Li, Jia, Liu, RuoYun, Xie, Fang, Su, YingYing, Chiang, YiChen, Zhao, BenHua, Cui, JingAn, Yin, Ling, Su, YanHua, Zhao, QingLong, Gao, LiDong, Chen, TianMu. A five-compartment model of age-specific transmissibility of SARS-CoV-2. 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ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE[J]. 2020, 47(6): 964-980, [16] Yin, Ling, Lin, Nan, Song, Xiaoqing, Mei, Shujiang, Shaw, ShihLung, Fang, Zhixiang, Li, Qinglan, Li, Ye, Mao, Liang. Space-time personalized short message service (SMS) for infectious disease control - Policies for precise public health. APPLIED GEOGRAPHY[J]. 2020, 114: http://dx.doi.org/10.1016/j.apgeog.2019.102103.[17] Xu, Yang, Li, Xinyu, Shaw, ShihLung, Lu, Feng, Yin, Ling, Chen, Bi Yu. Effects of Data Preprocessing Methods on Addressing Location Uncertainty in Mobile Signaling Data. ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS[J]. 2020, 111(2): 515-539, https://www.webofscience.com/wos/woscc/full-record/WOS:000553352100001.[18] 尹凌. Enhancing fine-grained intra-urban dengue forecasting by integrating spatial interacions of human movements between urban regions. PLOS Neglected Tropical Diseases. 2020, [19] Tianmu Chen, Jia Rui, Qiupeng Wang, Zeyu Zhao, Jingan Cui, Ling Yin. A mathematical model for simulating the transmission of Wuhan novel Coronavirus. bioRxivnull. 2020, https://doi.org/10.1101/2020.01.19.911669.[20] He Bing, Kong Bo, Yin Ling, Wu Qin, Hu Jinxing, Huang Dian, Ma Zhanwu. Discovering the Graph-Based Flow Patterns of Car Tourists Using License Plate Data: A Case Study in Shenzhen, China. JOURNAL OF ADVANCED TRANSPORTATION[J]. 2020, 2020: https://doaj.org/article/753165d3e6c14a4db9b28a1c9a945aee.[21] Chen, TianMu, Rui, Jia, Wang, QiuPeng, Zhao, ZeYu, Cui, JingAn, Yin, Ling. A mathematical model for simulating the phase-based transmissibility of a novel coronavirus. INFECTIOUS DISEASES OF POVERTY[J]. 2020, 9(1): http://lib.cqvip.com/Qikan/Article/Detail?id=7103820816.[22] 吕鸿鑫, 尹凌, 梅树江. 深圳市基层疾控机构突发公共卫生事件应急能力现况调查. 医学动物防制. 2020, 36(4): 356-359, http://lib.cqvip.com/Qikan/Article/Detail?id=7101674454.[23] Liu, Kang, Qiu, Peiyuan, Gao, Song, Lu, Feng, Jiang, Jincheng, Yin, Ling. 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PROCEEDINGS OF THE 2ND ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON AI FOR GEOGRAPHIC KNOWLEDGE DISCOVERY (GEOAI 2018)null. 2018, 19-28, http://dx.doi.org/10.1145/3281548.3281558.[38] 赵志远, 尹凌, 胡金星, 冯圣中, 黄思林. 面向机动车出行OD监测的目标路段选择算法. 地球信息科学学报[J]. 2018, 20(5): 656-664, http://lib.cqvip.com/Qikan/Article/Detail?id=675310155.[39] 尹凌. Identify stops in mobile phone location data with uncertainty analysis. 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A Spatial-Temporal Analysis of Users’ Geographical Patterns in Social Media: a Case Study on Microblogs. http://ir.siat.ac.cn:8080/handle/172644/6031.[79] []. Detecting Illegal Pickups of Intercity Buses from Their GPS Traces. http://ir.siat.ac.cn:8080/handle/172644/6065.[80] []. Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data. http://ir.siat.ac.cn:8080/handle/172644/10201.[81] []. A space-time GIS for dynamics in potential face-to-face meeting opportunities. http://ir.siat.ac.cn:8080/handle/172644/3596.