{"id":90,"date":"2017-08-14T05:59:50","date_gmt":"2017-08-14T05:59:50","guid":{"rendered":"http:\/\/216.24.255.190\/teamsite\/?page_id=90"},"modified":"2020-10-27T05:49:04","modified_gmt":"2020-10-27T05:49:04","slug":"pengpeng","status":"publish","type":"page","link":"http:\/\/pervasivegis.group\/teamsite\/members\/pengpeng\/","title":{"rendered":"\u5f6d\u6f8e"},"content":{"rendered":"<p><a><img loading=\"lazy\" width=\"165\" height=\"210\" class=\"size-full wp-image-56 aligncenter\" alt=\"\" src=\"http:\/\/pervasivegis.group\/teamsite\/wp-content\/uploads\/2020\/08\/pengpeng.jpg\"><\/a><\/p>\n<p style=\"font-size: 80%; text-align: center;\">\u25a0&nbsp; &nbsp;\u7535\u5b50\u90ae\u7bb1\uff1apengp@lreis.ac.cn<br \/>\n\u25a0&nbsp; &nbsp;\u5916\u90e8\u94fe\u63a5\uff1a<a href=\"https:\/\/scholar.google.com.hk\/citations?user=6IQ0fIIAAAAJ\">Google Scholar<\/a><\/p>\n<p style=\"text-indent: 2em;\">\u5f6d\u6f8e\uff0c\u7537\uff0c1989\u5e74\u751f\uff0c\u6e56\u5357\u5cb3\u9633\u4eba\uff0c\u535a\u58eb\uff0c\u4e2d\u56fd\u79d1\u5b66\u9662\u5730\u7406\u79d1\u5b66\u4e0e\u8d44\u6e90\u7814\u7a76\u6240\u535a\u58eb\u540e\u3001\u7279\u522b\u7814\u7a76\u52a9\u7406\u3002\u4e3b\u8981\u4ece\u4e8b\u590d\u6742\u7f51\u7edc\u5206\u6790\u3001\u6d77\u4e8b\u5927\u6570\u636e\u6316\u6398\u7b49\u7814\u7a76\u3002\u5df2\u53d1\u8868\u79d1\u7814\u8bba\u658723\u7bc7\uff0c\u7b2c\u4e00\u4f5c\u8005\/\u901a\u8baf\u4f5c\u8005\u8bba\u65879\u7bc7\uff0c\u7533\u8bf7\u6216\u6388\u6743\u53d1\u660e\u4e13\u522911\u9879\uff1b\u53d7\u9080\u62c5\u4efbSCI\u671f\u520aIJGI\u5ba2\u5ea7\u7f16\u8f91\u3001\u7b2c\u4e8c\u5c4a\u6d77\u4e8b\u5927\u6570\u636e\u56fd\u9645\u7814\u8ba8\u4f1a\u7ec4\u59d4\u4f1a\u6210\u5458\u3002\u5e76\u62c5\u4efbTransport Reviews, Transportation Research Part E, Ocean Engineering, Maritime Policy &amp; Management, Journal of Cleaner Production\u7b49\u9886\u57df\u4e3b\u6d41SCI\u671f\u520a\u5ba1\u7a3f\u4eba\u3002<\/p>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u7814\u7a76\u5174\u8da3<\/h3>\n<ul>\n<li>\u590d\u6742\u7f51\u7edc\u5206\u6790\u3001\u6d77\u4e8b\u5927\u6570\u636e\u6316\u6398<\/li>\n<\/ul>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u5de5\u4f5c\u7ecf\u5386<\/h3>\n<ul>\n<li>2019\u5e747\u6708-\u81f3\u4eca\uff0c\u4e2d\u56fd\u79d1\u5b66\u9662\u5730\u7406\u79d1\u5b66\u4e0e\u8d44\u6e90\u7814\u7a76\u6240\uff0c\u535a\u58eb\u540e\u3001\u7279\u522b\u7814\u7a76\u52a9\u7406\uff0c\u5408\u4f5c\u5bfc\u5e08\uff1a\u9646\u950b<\/li>\n<\/ul>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u5b66\u4e60\u7ecf\u5386<\/h3>\n<ul>\n<li>2015\u5e749\u6708-2019\u5e746\u6708\uff0c\u4e2d\u56fd\u79d1\u5b66\u9662\u5730\u7406\u79d1\u5b66\u4e0e\u8d44\u6e90\u7814\u7a76\u6240\uff0c\u535a\u58eb\uff0c\u5bfc\u5e08\uff1a\u9646\u950b<\/li>\n<li>2011\u5e749\u6708-2013\u5e746\u6708\uff0c\u6b66\u6c49\u5927\u5b66\uff0c\u7855\u58eb\uff0c\u5bfc\u5e08\uff1a\u6731\u6b23\u7130<\/li>\n<li>2007\u5e749\u6708-2011\u5e746\u6708\uff0c\u6cb3\u6d77\u5927\u5b66\uff0c\u5b66\u58eb<\/li>\n<\/ul>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u53d1\u8868\u8bba\u8457<\/h3>\n<ol>\n<li>Peng Peng, Shifen Cheng, Feng Lu*. 2020. Characterizing the global liquefied petroleum gas trading community using mass vessel trajectory data. <em>Journal of Cleaner Production<\/em>,  252: 119883. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.jclepro.2019.119883\">10.1016\/j.jclepro.2019.119883<\/a> [<a href=\"http:\/\/pervasivegis.group\/teamsite\/literatures\/characterizing-the-global-liquefied-petroleum-gas-trading-community-using-mass-vessel-trajectory-data\/\" target=\"_blank\" rel=\"noopener noreferrer\">Abstract<\/a>]<\/li>\n<li>Peng Peng, Yu Yang, Shifen Cheng, Feng Lu*, Zimu Yuan. 2019. Hub-and-spoke structure: Characterizing the global crude oil transport network with mass vessel trajectories. <em>Energy<\/em>,  168: 966-974. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.energy.2018.11.049\">10.1016\/j.energy.2018.11.049<\/a><\/li>\n<li>Peng Peng, Jessie P. H. Poon, Yu Yang**, Feng Lu*, Shifen Cheng. 2019. Global oil traffic network and diffusion of influence among ports using real time data. <em>Energy<\/em>,  172: 333-342. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.energy.2019.01.118\">10.1016\/j.energy.2019.01.118<\/a><\/li>\n<li>Peng Peng, Yu Yang, Feng Lu*, Shifen Cheng, Naixia Mou, Ren Yang. 2018. Modelling the competitiveness of the ports along the Maritime Silk Road with big data. <em>Transportation Research Part A: Policy and Practice<\/em>,  118: 852-867. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.tra.2018.10.041\">10.1016\/j.tra.2018.10.041<\/a><\/li>\n<li>Peng Peng, Shifen Cheng, Jinhai Chen, Mengdi Liao, Lin Wu, Xiliang Liu, Feng Lu*. 2018. A fine-grained perspective on the robustness of global cargo ship transportation networks. <em>Journal of Geographical Sciences<\/em>,  28(7): 881-889. doi: <a href=\"https:\/\/doi.org\/10.1007\/s11442-018-1511-z\">10.1007\/s11442-018-1511-z<\/a><\/li>\n<li>Peng Peng, Feng Lu*. 2020. Mapping the Port Influence Diffusion Patterns: A Case Study of Rotterdam, Antwerp and Singapore. In <em>Proceedings of the 20th International Conference on Computational Science (ICCS 2020)<\/em>,  Amsterdam, The Netherlands: 266\u2013276. doi: <a href=\"https:\/\/doi.org\/10.1007\/978-3-030-50423-6_20\">10.1007\/978-3-030-50423-6_20<\/a> [<a href=\"http:\/\/pervasivegis.group\/teamsite\/literatures\/mapping-the-port-influence-diffusion-patterns-a-case-study-of-rotterdam-antwerp-and-singapore\/\" target=\"_blank\" rel=\"noopener noreferrer\">Abstract<\/a>]<\/li>\n<li>\u5f6d\u6f8e, \u7a0b\u8bd7\u594b, \u5218\u5e0c\u4eae, \u6885\u5f3a, \u9646\u950b*. 2017. \u5168\u7403\u6d77\u6d0b\u8fd0\u8f93\u7f51\u7edc\u5065\u58ee\u6027\u8bc4\u4f30. <em>\u5730\u7406\u5b66\u62a5<\/em>,  72(12): 2241-2251. doi: <a href=\"http:\/\/www.geog.com.cn\/CN\/10.11821\/dlxb201712009\">10.11821\/dlxb201712009<\/a> [<a href=\"http:\/\/pervasivegis.group\/teamsite\/literatures\/\u5168\u7403\u6d77\u6d0b\u8fd0\u8f93\u7f51\u7edc\u5065\u58ee\u6027\u8bc4\u4f30\/\" target=\"_blank\" rel=\"noopener noreferrer\">Abstract<\/a>]<\/li>\n<li>\u9648\u95ea\u95ea, \u5f6d\u6f8e*, \u9646\u950b, \u5434\u5347. 2019. \u6d77\u6d0b\u4e3b\u822a\u9053\u5bf9\u5168\u7403\u96c6\u88c5\u7bb1\u8fd0\u8f93\u7f51\u7edc\u7684\u5f71\u54cd\u5206\u6790. <em>\u5730\u7406\u7814\u7a76<\/em>,  38(9): 2273-2287. doi: <a href=\"https:\/\/doi.org\/10.11821\/dlyj020181375\">10.11821\/dlyj020181375<\/a><\/li>\n<li>\u5f6d\u6f8e, \u7a0b\u8bd7\u594b, \u9648\u95ea\u95ea, \u9646\u950b. 2020. \u5168\u7403\u6db2\u5316\u77f3\u6cb9\u6c14\u8fd0\u8f93\u7f51\u7edc\u8d38\u6613\u793e\u533a\u7279\u5f81\u53ca\u5176\u6f14\u5316\u5206\u6790. <em>\u81ea\u7136\u8d44\u6e90\u5b66\u62a5<\/em>,  (\u5f55\u7528\u5f85\u520a).<\/li>\n<li>Shifen Cheng, Feng Lu*, Peng Peng. 2020. Short-term traffic forecasting by mining the non-stationarity of spatiotemporal patterns. <em>IEEE Transactions on Intelligent Transportation Systems<\/em>,  (Early Access): 1-19. doi: <a href=\"https:\/\/doi.org\/10.1109\/TITS.2020.2991781\">10.1109\/TITS.2020.2991781<\/a><\/li>\n<li>Shifen Cheng, Peng Peng, Feng Lu*. 2020. A lightweight ensemble spatiotemporal interpolation model for geospatial data. <em>International Journal of Geographical Information Science<\/em>,  (Early Access): 1-24. doi: <a href=\"https:\/\/doi.org\/10.1080\/13658816.2020.1725016\">10.1080\/13658816.2020.1725016<\/a><\/li>\n<li>Shifen Cheng, Feng Lu*, Peng Peng. 2020. A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China. <em>Journal of Cleaner Production<\/em>,  250: 119445. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.jclepro.2019.119445\">10.1016\/j.jclepro.2019.119445<\/a><\/li>\n<li>Shifen Cheng, Beibei Zhang, Peng Peng, Zhenzhen Yang, Feng Lu*. 2020. Spatiotemporal evolution pattern detection for heavy-duty diesel truck emissions using trajectory mining: A case study of Tianjin, China. <em>Journal of Cleaner Production<\/em>,  244: 118654. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.jclepro.2019.118654\">10.1016\/j.jclepro.2019.118654<\/a><\/li>\n<li>Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu. 2019. Multi-task and multi-view learning based on particle swarm optimization for short-term traffic forecasting. <em>Knowledge-Based Systems<\/em>,  180: 116-132. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.knosys.2019.05.023\">10.1016\/j.knosys.2019.05.023<\/a><\/li>\n<li>Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu. 2018. Short-term traffic forecasting: An adaptive ST-KNN model that considers spatial heterogeneity. <em>Computers, Environment and Urban Systems<\/em>, 71: 186-198. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.compenvurbsys.2018.05.009\">10.1016\/j.compenvurbsys.2018.05.009<\/a><\/li>\n<li>Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu. 2018. A spatiotemporal multi-view-based learning method for short-term traffic forecasting. <em>ISPRS International Journal of Geo-Information<\/em>,  7(6): 218. doi: <a href=\"https:\/\/doi.org\/10.3390\/ijgi7060218\">10.3390\/ijgi7060218<\/a><\/li>\n<li>Beibei Zhang, Sheng Wu, Shifen Cheng*, Feng Lu, Peng Peng. 2019. Spatial characteristics and factor analysis of pollution emission from heavy-duty diesel trucks in the Beijing-Tianjin-Hebei region, China. <em>International Journal of Environmental Research and Public Health<\/em>,  16(24): 4973. doi: <a href=\"https:\/\/doi.org\/10.3390\/ijerph16244973\">10.3390\/ijerph16244973<\/a><\/li>\n<li>Naixia Mou, Caixia Liu*, Lingxian Zhang, Xin Fu*, Yichun Xie, Yong Li, Peng Peng. 2018. Spatial pattern and regional relevance analysis of the Maritime Silk Road shipping network. <em>Sustainability<\/em>,  10(4): 977. doi: <a href=\"https:\/\/doi.org\/10.3390\/su10040977\">10.3390\/su10040977<\/a><\/li>\n<li>Hongchu Yu, Zhixiang Fang*, Feng Lu, Alan T. Murray, Hengcai Zhang, Peng Peng, Qiang Mei, Jinhai Chen. 2019. Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes.<em>Applied Energy<\/em>,  237: 390-403. doi: <a href=\"https:\/\/doi.org\/10.1016\/j.apenergy.2019.01.011\">10.1016\/j.apenergy.2019.01.011<\/a> [<a href=\"http:\/\/pervasivegis.group\/teamsite\/literatures\/impact-of-oil-price-fluctuations-on-tanker-maritime-network-structure-and-traffic-flow-changes\/\" target=\"_blank\" rel=\"noopener noreferrer\">Abstract<\/a>]<\/li>\n<li>\u6768\u5fcd, \u725f\u4e43\u590f*, \u5f6d\u6f8e, \u5218\u5e0c\u4eae, \u5f20\u6052\u624d, \u9646\u950b. 2018. \u201c\u6d77\u4e0a\u4e1d\u7ef8\u4e4b\u8def\u201d \u6cbf\u7ebf\u91cd\u8981\u6e2f\u53e3\u7ade\u4e89\u529b\u8bc4\u4ef7. <em>\u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5<\/em>,  20(5): 623-631. doi: <a href=\"http:\/\/www.dqxxkx.cn\/CN\/10.12082\/dqxxkx.2018.170515\">10.12082\/dqxxkx.2018.170515<\/a><\/li>\n<li>\u6885\u5f3a, \u5434\u7433, \u5f6d\u6f8e, \u5468\u9e4f, \u9648\u91d1\u6d77*. 2018. \u5357\u6d77\u533a\u57df\u5546\u8239\u5178\u578b\u7a7a\u95f4\u5206\u5e03\u53ca\u8d38\u6613\u6d41\u5411\u7814\u7a76. <em>\u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5<\/em>,  20(5): 632\u2013639. doi: <a href=\"http:\/\/www.dqxxkx.cn\/CN\/10.12082\/dqxxkx.2018.180017\">10.12082\/dqxxkx.2018.180017<\/a><\/li>\n<li>\u725f\u4e43\u590f, \u5ed6\u68a6\u8fea, \u5f20\u6052\u624d*, \u5f6d\u6f8e, \u5218\u5e0c\u4eae. 2018. \u201c\u6d77\u4e0a\u4e1d\u7ef8\u4e4b\u8def\u201d \u6cbf\u7ebf\u91cd\u8981\u6e2f\u53e3\u533a\u4f4d\u4f18\u52bf\u5ea6\u8bc4\u4f30. <em>\u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5<\/em>,  20(5): 613\u2013622. doi: <a href=\"http:\/\/www.dqxxkx.cn\/CN\/10.12082\/dqxxkx.2018.170514\">10.12082\/dqxxkx.2018.170514<\/a><\/li>\n<li>\u4f59\u7ea2\u695a, \u65b9\u5fd7\u7965*, \u9646\u950b, \u5f6d\u6f8e, \u8d75\u5fd7\u8fdc, \u51af\u660e\u7fd4. 2018. \u91cd\u8981\u7ecf\u6d4e\u53d1\u5c55\u533a\u57df\u95f4\u6d77\u8fd0\u7f51\u7edc\u65f6\u7a7a\u6f14\u53d8\u7279\u6027\u5206\u6790. <em>\u5730\u7403\u4fe1\u606f\u79d1\u5b66\u5b66\u62a5<\/em>,  20(5): 1-11. doi: <a href=\"http:\/\/www.dqxxkx.cn\/CN\/10.12082\/dqxxkx.2018.180085\">10.12082\/dqxxkx.2018.180085<\/a><\/li>\n<\/ol>\n<hr>\n<h3 style=\"color: #0c6eb6;\">\u79d1\u7814\u9879\u76ee<\/h3>\n<ol>\n<li>\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u9752\u5e74\u57fa\u91d1\u9879\u76ee\uff0c\u5168\u7403\u6d77\u6d0b\u6cb9\u6c14\u8fd0\u8f93\u7f51\u7edc\u7ed3\u6784\u7279\u5f81\u3001\u52a8\u6001\u5065\u58ee\u6027\u53ca\u5173\u952e\u6e2f\u53e3\u5f71\u54cd\u529b\u7814\u7a76, 2021.01-2023.12\uff0c\u5728\u7814, \u4e3b\u6301.<\/li>\n<li>\u4e2d\u56fd\u79d1\u5b66\u9662\u7279\u522b\u7814\u7a76\u52a9\u7406\u9879\u76ee, \u591a\u5c42\u7f51\u7edc\u89c6\u89d2\u4e0b\u5168\u7403\u6d77\u6d0b\u6cb9\u6c14\u8fd0\u8f93\u683c\u5c40\u53ca\u5176\u6f14\u5316\u7814\u7a76, 2020.01-2022.12, \u5728\u7814, \u4e3b\u6301.<\/li>\n<li>\u4e2d\u56fd\u535a\u58eb\u540e\u79d1\u5b66\u57fa\u91d1\u9762\u4e0a\u9879\u76ee\u7b2c66\u6279, 2020.01-2022.6, \u5728\u7814, \u4e3b\u6301.<\/li>\n<li>\u4e2d\u56fd\u535a\u58eb\u540e\u79d1\u5b66\u57fa\u91d1\u7279\u522b\u8d44\u52a9\u7b2c13\u6279, 2020.08-2022.6, \u5728\u7814, \u4e3b\u6301.<\/li>\n<li>\u4e2d\u56fd\u79d1\u5b66\u9662\u6218\u7565\u6027\u5148\u5bfc\u79d1\u6280\u4e13\u9879, \u751f\u6001\u6587\u660e\u5efa\u8bbe\u5730\u7406\u56fe\u666f\u6280\u672f\u4e0e\u5e94\u7528\u793a\u8303, 2019.01-2023.12, \u5728\u7814, \u53c2\u4e0e.<\/li>\n<li>\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u59d4\u5458\u4f1a\u91cd\u70b9\u57fa\u91d1\u9879\u76ee, \u7f51\u7edc\u6587\u672c\u8574\u542b\u5730\u7406\u4fe1\u606f\u7406\u89e3\u4e0e\u77e5\u8bc6\u56fe\u6784\u5efa, 2017.01-2021.12, \u5728\u7814, \u53c2\u4e0e.<\/li>\n<li>\u4e2d\u56fd\u79d1\u5b66\u9662\u91cd\u70b9\u90e8\u7f72\u8bfe\u9898, \u5317\u6781\u822a\u9053\u6f14\u53d8\u5bf9\u5730\u7f18\u73af\u5883\u5f71\u54cd, 2017.01-2020.12, \u5728\u7814, \u53c2\u4e0e.<\/li>\n<li>\u4e2d\u56fd\u79d1\u5b66\u9662\u91cd\u70b9\u90e8\u7f72\u8bfe\u9898, \u5370\u5ea6\u6d0b\u6e2f\u53e3\u5730\u7f18\u4f18\u52bf\u5206\u6790\u4e0e\u8fd0\u8f93\u6001\u52bf\u52a8\u6001\u8bc4\u4f30, 2016.01-2019.12, \u5df2\u7ed3\u9898\uff0c\u53c2\u4e0e.<\/li>\n<\/ol>\n<hr>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u25a0&nbsp; &nbsp;\u7535\u5b50\u90ae\u7bb1\uff1apengp@lreis.ac.cn \u25a0&nbsp; &nbsp;\u5916\u90e8\u94fe\u63a5 <a href=\"http:\/\/pervasivegis.group\/teamsite\/members\/pengpeng\/\" rel=\"nofollow\"><span class=\"sr-only\">Read more about \u5f6d\u6f8e<\/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\/90"}],"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=90"}],"version-history":[{"count":27,"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/pages\/90\/revisions"}],"predecessor-version":[{"id":1500,"href":"http:\/\/pervasivegis.group\/teamsite\/wp-json\/wp\/v2\/pages\/90\/revisions\/1500"}],"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=90"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}