Article(id=1242136682217153244, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242136669516804758, articleNumber=null, orderNo=11, doi=10.3981/j.issn.1000-7857.2018.03.009, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1510416000000, receivedDateStr=2017-11-12, revisedDate=1516032000000, revisedDateStr=2018-01-16, acceptedDate=null, acceptedDateStr=null, onlineDate=1519894753640, onlineDateStr=2018-03-01, pubDate=1518451200000, pubDateStr=2018-02-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1519894753640, onlineIssueDateStr=2018-03-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774078062820, creator=sys-migrate, updateTime=1774078062820, updator=sys-migrate, issue=Issue{id=1242136669516804758, tenantId=1146029695717560320, journalId=1146031591421210625, year='2018', volume='36', issue='3', pageStart='1', pageEnd='124', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774078059792, creator=sys-migrate, updateTime=1774078059792, updator=sys-migrate, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=70, endPage=74, ext={EN=ArticleExt(id=1242136684972810999, articleId=1242136682217153244, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Intelligent recognition of risk levels of geopolitical system for South Asia, columnId=1242116903087440448, journalTitle=Science & Technology Review, columnName=Spescial Issues, runingTitle=null, highlight=null, articleAbstract=A fast and accurate recognition of risk levels of geopolitical system for the typical regions of "the Belt and Road Initiative" can provide scientific support for the geopolitical strategy. The geopolitical system is not only influenced by climate and geographic environment but also hemmed by nationality, religion, civilization, ideology, political system and development level. Solutions to those problems not only depend on interdisciplinary work but also need cross-border study. Based on the geosystem theory, this paper makes a systematic study of literature, and firstly presents an evaluation index system for geopolitical risks. Then, it provides a machine learning method to evaluate the geopolitical risk levels of South Asia region based on the multiscale and multidata sources global geo-environment database. It is expected to provide a scientific support for the China Pakistan Economic Corridor(CPEC)., correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=AeLeJNcGZDKg+jH+WajOcQ==, pdfFileSize=1033245, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
2. College of Resource and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;
3. School of Earth Science and Resource, Chang'an University, Xi'an 710064, China;
4. College of Geoscience and Surveying Engineering, China University of Mining & Technology(Beijing), Beijing 100083, China, fund=null, authors=LIN Gang¹, DING Fangyu^1,2, FU Jingying^1,2, YANG Xuefei³, HAN Quan⁴, authorsList=LIN Gang, DING Fangyu, FU Jingying, YANG Xuefei, HAN Quan), CN=ArticleExt(id=1242136683991343848, articleId=1242136682217153244, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=南亚地缘环境风险等级的智能判别与分析, columnId=1242116902361830275, journalTitle=科技导报, columnName=专题论文, runingTitle=null, highlight=null, articleAbstract=地缘环境安全受到地形、气候、资源等自然要素的制约，也受到民族、宗教、文明、意识形态、政治制度、发展水平等差异的影响。基于地缘风险系统理论，梳理了历史研究成果，确立了地缘风险评价指标体系。以最新建立的多尺度、多数据源的全球地缘环境数据库为本底，以南亚为典型区域，构建了基于机器学习算法的地缘风险智能评价模型。, correspAuthors=null, authorNote=林刚,博士后,研究方向为遥感与空间信息技术在水资源开发管理中的应用,电子信箱:ling@lreis.ac.cn, correspAuthorsNote=付晶莹(通信作者),副研究员,研究方向为资源环境遥感应用,电子信箱:fujy@igsnrr.ac.cn, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=11vxdMlXoci4lflBmgV3lw==, pdfFileSize=1033245, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=1. 中国科学院地理科学与资源研究所, 北京 100101;
2. 中国科学院大学资源与环境学院, 北京 100049;
3. 长安大学地球科学与资源学院, 西安 710064;
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