{"id":89,"date":"2017-08-14T05:59:19","date_gmt":"2017-08-14T05:59:19","guid":{"rendered":"http:\/\/216.24.255.190\/teamsite\/?page_id=89"},"modified":"2020-08-18T13:29:35","modified_gmt":"2020-08-18T13:29:35","slug":"limingxiao","status":"publish","type":"page","link":"http:\/\/pervasivegis.group\/teamsite\/members\/limingxiao\/","title":{"rendered":"\u674e\u660e\u6653"},"content":{"rendered":"<p><a><img loading=\"lazy\" class=\"size-full wp-image-56 aligncenter\" src=\"http:\/\/pervasivegis.group\/teamsite\/wp-content\/uploads\/2020\/08\/limingxiao.jpg\" alt=\"\" width=\"165\" height=\"210\"><\/a><\/p>\n<p style=\"font-size: 80%; text-align: center;\">\u25a0&nbsp; &nbsp;\u7535\u5b50\u90ae\u7bb1\uff1alimx@lreis.ac.cn<br \/>\n\u25a0&nbsp; &nbsp;\u5916\u90e8\u94fe\u63a5\uff1a<a href=\"https:\/\/scholar.google.com.hk\/citations?user=CWbmj6EAAAAJ\">Google Scholar<\/a><\/p>\n<p style=\"text-indent: 2em;\">\u674e\u660e\u6653\uff0c\u7537\uff0c1991\u5e74\u751f\uff0c\u5409\u6797\u957f\u6625\u4eba\uff0c\u535a\u58eb\uff0c\u6df1\u5733\u5927\u5b66\u5efa\u7b51\u4e0e\u57ce\u5e02\u89c4\u5212\u5b66\u9662\u535a\u58eb\u540e\u3002\u7814\u7a76\u65b9\u5411\u4e3a\u4eba\u7c7b\u79fb\u52a8\u6027\uff0c\u8f68\u8ff9\u6570\u636e\u6316\u6398\uff0c\u667a\u6167\u57ce\u5e02\u7b49\u3002\u5728\u535a\u58eb\u9636\u6bb5\u5171\u53d1\u8868\u79d1\u7814\u8bba\u658717\u7bc7\uff0c\u5176\u4e2d\u7b2c\u4e00\u4f5c\u8005\u8bba\u65877\u7bc7\uff08SCI\/SSCI\u8bba\u65873\u7bc7\uff09\uff0c\u64b0\u5199\u53d1\u660e\u4e13\u52295\u9879\u3002\u62c5\u4efbPlos One\u3001IEEE Access\u3001Open Geosciences\u3001ACM SIGSPATIAL\u3001\u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5\u7b49\u671f\u520a\u4e0e\u4f1a\u8bae\u5ba1\u7a3f\u4eba\u3002<\/p>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u7814\u7a76\u5174\u8da3<\/h3>\n<ul>\n<li>\u4eba\u7c7b\u79fb\u52a8\u6027\u4e0e\u667a\u6167\u57ce\u5e02\u3001\u8f68\u8ff9\u6570\u636e\u6316\u6398\u4e0e\u53ef\u89c6\u5316<\/li>\n<\/ul>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u5de5\u4f5c\u7ecf\u5386<\/h3>\n<ul>\n<li>2020\u5e747\u6708-\u81f3\u4eca\uff0c\u6df1\u5733\u5927\u5b66\u5efa\u7b51\u4e0e\u57ce\u5e02\u89c4\u5212\u5b66\u9662\uff0c\u535a\u58eb\u540e\uff0c\u5408\u4f5c\u5bfc\u5e08\uff1a\u6d82\u4f1f<\/li>\n<\/ul>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u5b66\u4e60\u7ecf\u5386<\/h3>\n<ul>\n<li>2018\u5e7411\u6708-2019\u5e7411\u6708\uff0c\u5a01\u65af\u5eb7\u661f\u5927\u5b66\u9ea6\u8fea\u900a\u5206\u6821\uff0c\u5730\u7406\u4fe1\u606f\u7cfb\u7edf\uff0c\u8bbf\u95ee\u5b66\u8005\uff0c\u5bfc\u5e08\uff1a\u9ad8\u677e<\/li>\n<li>2014\u5e749\u6708-2020\u5e746\u6708\uff0c\u4e2d\u56fd\u79d1\u5b66\u9662\u5730\u7406\u79d1\u5b66\u4e0e\u8d44\u6e90\u7814\u7a76\u6240\uff0c\u5730\u56fe\u5b66\u4e0e\u5730\u7406\u4fe1\u606f\u7cfb\u7edf\uff0c\u7406\u5b66\u535a\u58eb\uff0c\u5bfc\u5e08\uff1a\u9646\u950b<\/li>\n<li>2010\u5e749\u6708-2014\u5e746\u6708\uff0c\u6b66\u6c49\u5927\u5b66\u8d44\u6e90\u4e0e\u73af\u5883\u79d1\u5b66\u5b66\u9662\uff0c\u5730\u56fe\u5b66\u4e0e\u5730\u7406\u4fe1\u606f\u7cfb\u7edf\uff0c\u7406\u5b66\u535a\u58eb<\/li>\n<\/ul>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u53d1\u8868\u8bba\u8457<\/h3>\n<ol>\n<li>Li Mingxiao, Gao Song, Lu Feng and Zhang Hengcai. 2019. Dynamic estimation of individual exposure levels to air pollution using trajectories reconstructed from mobile phone data. International Journal of Environmental Research and Public Health. Int. J. Environ. Res. Public Health 16, 22: 4522.<\/li>\n<li>Li Mingxiao, Gao Song, Lu Feng and Zhang Hengcai. 2019. Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data. Computers, Environment and Urban Systems, 77: 101346.<\/li>\n<li>Li Mingxiao, Lu Feng, Zhang Hengcai and Chen Jie. 2018. Predicting future locations of moving objects with deep fuzzy-LSTM networks. Transportmetrica A: Transport Science: 1-18.<\/li>\n<li>Li Mingxiao, Zhang Hengcai, Jie Chen. 2019. Fine-grained Dynamic Population Mapping Method Based on Large-scale Sparse Mobile Phone Data. IEEE International Conference on Mobile Data Management (MDM). IEEE: 473-478.<\/li>\n<li>Li Mingxiao, Gao Song, Liang Yunlei, Joseph Marks, Kang Yuhao, and Li. 2019 Moyin. A Data-Driven Approach to Understanding and Predicting the Spatiotemporal Availability of Street Parking. In 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Chicago, IL, ACM, 4 pages.<\/li>\n<li>Liu Xiliang, Liu Kang, Li Mingxiao and Lu Feng. 2017. A ST-CRF Map-Matching Method for Low-Frequency Floating Car Data. IEEE Transactions on Intelligent Transportation Systems 18, 5:1241-1254.<\/li>\n<li>Liang Yunlei, Gao Song, Li Mingxiao, Kang Yuhao, and Rao Jinmeng. 2018. Analyzing the Gap Between Ride-hailing Location and Pick-up Location with Geographical Contexts. In 1st ACM SIGSPATIAL International Workshop on Ride-hailing Algorithms, Applications, and Systems (RAAS \u201919).ACM, New York, NY, USA, 4 pages. (Accepted)<\/li>\n<li>Liu Xilang, Liu Kang, Li Mingxiao, Lu Feng, Liao Mengdi and Yang Ren. 2017. SHE: Stepwise Heterogeneous Ensemble Method for Citywide Traffic Analysis. ACM SIGSPATIAL Workshop on Prediction of Human Mobility. ACM: 3.<\/li>\n<li>Liu Kang, Qiu Peiyuan, Li Mingxiao and Lu Feng. 2016. Exploring urban travel routes' characteristics from a geometric perspective. 2016 24th International Conference on Geoinformatics. IEEE: 1-6.<\/li>\n<li>Yu Li, Liu Xiliang, Li Mingxiao, Peng Peng and Lu Feng. 2016. A holistic framework of geographical semantic web aligning. Proceedings of the 10th Workshop on Geographic Information Retrieval. ACM: 1.<\/li>\n<li>Chen Jinhai, Lu Feng, Li Mingxiao, Pengfei Huang, Xiliang Liu, and Qiang Mei. 2016. Optimization on arrangement of precaution areas serving for ships\u2019 routeing in the Taiwan strait based on massive AIS data. Data Mining and Big Data: 123-133.<\/li>\n<li>Chen Jie, Pei Tao, Shih-Lung Shaw, Lu Feng, Li Mingxiao, Cheng Shifen, Liu Xiliang, and Zhang Hengcai. 2018. Fine-grained prediction of urban population using mobile phone location data. IJGIS 32, 9:1770-1786.<\/li>\n<li>Liu Xiliang, Lu Feng, Liu Kang, Qiu Peiyuan, Yu Li, and Li Mingxiao. 2016. A Principal Curve-based method for Geospatial Data Smoothing. In International Conference on GIScience Short Paper Proceedings 1, 1.<\/li>\n<li>\u674e\u660e\u6653, \u5f20\u6052\u624d, \u4ec7\u57f9\u5143, \u7a0b\u8bd7\u594b, \u9648\u6d01, \u9646\u950b\uff0e2018. \u4e00\u79cd\u57fa\u4e8e\u6a21\u7cca\u957f\u77ed\u671f\u795e\u7ecf\u7f51\u7edc\u7684\u79fb\u52a8\u5bf9\u8c61\u8f68\u8ff9\u9884\u6d4b\u7b97\u6cd5\uff0e\u6d4b\u7ed8\u5b66\u62a5 47, 12: 1660-1669.<\/li>\n<li>\u674e\u660e\u6653, \u9648\u6d01, \u5f20\u6052\u624d, \u4ec7\u57f9\u5143, \u5218\u5eb7, \u9646\u950b. 2017. \u4e0a\u6d77\u5e02\u7cbe\u7ec6\u65f6\u7a7a\u5c3a\u5ea6\u4eba\u53e3\u5206\u5e03\u4f30\u8ba1\u4e0e\u7279\u5f81\u5206\u6790. \u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5, 06: 82 &#8211; 89.<\/li>\n<li>\u9648\u91d1\u6d77, \u9646\u950b, \u674e\u660e\u6653. 2015. \u6d77\u4e0a\u4e3b\u822a\u8ff9\u5e26\u8fb9\u754c\u7edf\u8ba1\u63a8\u65ad\u4e0e\u6d77\u897f\u822a\u8def\u8b66\u6212\u533a\u5e03\u5c40\u4f18\u5316\u5206\u6790. \u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5 17, 10: 1196 &#8211; 1206<\/li>\n<li>\u9648\u4e3d\u5a1c, \u5434\u5347, \u9648\u6d01, \u674e\u660e\u6653, \u9646\u950b. 2018. \u57fa\u4e8e\u624b\u673a\u5b9a\u4f4d\u6570\u636e\u7684\u57ce\u5e02\u4eba\u53e3\u5206\u5e03\u8fd1\u5b9e\u65f6\u9884\u6d4b. \u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5 20, 4: 523 &#8211; 531.<\/li>\n<\/ol>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u79d1\u7814\u9879\u76ee<\/h3>\n<ol>\n<li>\u56fd\u5bb6\u91cd\u70b9\u7814\u53d1\u8ba1\u5212\uff0c\u5ba4\u5185\u9ad8\u7cbe\u5ea6\u6d4b\u56fe\u4e0e\u5b9e\u65f6 GIS \u6280\u672f<\/li>\n<li>\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u9762\u4e0a\u9879\u76ee\uff0c\u57ce\u5e02\u4eba\u7fa4\u79fb\u52a8\u805a\u96c6\u4e0e\u7ed3\u6784\u52a8\u6001\u6a21\u5f0f\u5206\u6790\u65b9\u6cd5<\/li>\n<\/ol>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u7533\u8bf7\u4e13\u5229<\/h3>\n<ol>\n<li>\u5f20\u6052\u624d, \u674e\u660e\u6653, \u9646\u950b, \u4ec7\u57f9\u5143, \u5f6d\u5f6d, \u7a0b\u8bd7\u594b. \u4e00\u79cd\u4eba\u7c7b\u51fa\u884c\u7cfb\u6570\u8f68\u8ff9\u6570\u636e\u63d2\u503c\u91cd\u6784\u65b9\u6cd5: CN201910672777.5.<\/li>\n<li>\u5f20\u6052\u624d, \u674e\u660e\u6653, \u9646\u950b. \u4e00\u79cd\u51fa\u884c\u672a\u6765\u8f68\u8ff9\u9884\u6d4b\u65b9\u6cd5\u3001\u88c5\u7f6e\u3001\u50a8\u5b58\u4ecb\u8d28\u53ca\u7535\u5b50\u8bbe\u5907: CN201910667629.4.<\/li>\n<li>\u9648\u6d01, \u88f4\u97ec, \u674e\u660e\u6653. \u4e00\u79cd\u57fa\u4e8e\u624b\u673a\u6570\u636e\u7684\u57ce\u5e02\u4eba\u7fa4\u758f\u6563\u98ce\u9669\u52a8\u6001\u8bc4\u4ef7\u65b9\u6cd5: CN201810765665.X.<\/li>\n<li>\u9648\u6d01, \u88f4\u97ec, \u9646\u950b, \u674e\u660e\u6653, \u7a0b\u8bd7\u594b. \u4e00\u79cd\u57fa\u4e8e\u624b\u673a\u6570\u636e\u7684\u7cbe\u7ec6\u5c3a\u5ea6\u57ce\u5e02\u4eba\u7fa4\u6570\u91cf\u9884\u6d4b\u65b9\u6cd5: CN201711353043.8.<\/li>\n<li>\u9646\u950b, \u5218\u5e0c\u4eae, \u5f6d\u6f8e, \u5218\u5eb7, \u674e\u660e\u6653, \u725f\u4e43\u590f. \u4e00\u79cd\u9762\u5411\u7a00\u758f\u6d6e\u52a8\u8f66\u6570\u636e\u6761\u4ef6\u7684\u968f\u673a\u573a\u5730\u56fe\u5339\u914d\u65b9\u6cd5: CN201610135201.1.<\/li>\n<\/ol>\n<hr>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u25a0&nbsp; &nbsp;\u7535\u5b50\u90ae\u7bb1\uff1alimx@lreis.ac.cn \u25a0&nbsp; &nbsp;\u5916\u90e8\u94fe\u63a5\uff1a <a href=\"http:\/\/pervasivegis.group\/teamsite\/members\/limingxiao\/\" rel=\"nofollow\"><span class=\"sr-only\">Read more about \u674e\u660e\u6653<\/span>[&hellip;]<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":857,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/pages\/89"}],"collection":[{"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/comments?post=89"}],"version-history":[{"count":17,"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/pages\/89\/revisions"}],"predecessor-version":[{"id":1245,"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/pages\/89\/revisions\/1245"}],"up":[{"embeddable":true,"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/pages\/857"}],"wp:attachment":[{"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/media?parent=89"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}