Article(id=1242136092724502588, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242136140153692391, articleNumber=null, orderNo=13, doi=10.3981/j.issn.1000-7857.2017.11.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1488384000000, receivedDateStr=2017-03-02, revisedDate=1497456000000, revisedDateStr=2017-06-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1497418017337, onlineDateStr=2017-06-14, pubDate=1499875200000, pubDateStr=2017-07-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1500280157520, onlineIssueDateStr=2017-07-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774077922274, creator=sys-migrate, updateTime=1774077938066, updator=sys-migrate, issue=Issue{id=1242136140153692391, tenantId=1146029695717560320, journalId=1146031591421210625, year='2017', volume='35', issue='13', pageStart='1', pageEnd='104', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774077933583, creator=sys-migrate, updateTime=1774077933583, updator=sys-migrate, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=52, endPage=56, ext={EN=ArticleExt(id=1242136098529419352, articleId=1242136092724502588, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Methods of data assimilation for environmental atmosphere and their applications, columnId=1242116903087440448, journalTitle=Science & Technology Review, columnName=Spescial Issues, runingTitle=null, highlight=null, articleAbstract=From the perspective of data assimilation, we analyze some useful technologies including Kalman filter, meta-heuristics algorithm, Bayesian inference, non parametric regression, and traditional optimization method，and summarize their applications to the environmental monitoring data assimilation problem. The paper shows that different methods can be applied to solve the environmental monitoring data assimilation problems, and that the meta-heuristics algorithm combined with the traditional optimization method has a hopeful future in this field., correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=/amvU6aRljHkMg3o3IoBPQ==, pdfFileSize=1585555, 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=China Institute for Radiation Protection, Taiyuan 030006, China, fund=null, authors=XU Xiangjun, YAO Rentai, CHEN Longquan, authorsList=XU Xiangjun, YAO Rentai, CHEN Longquan), CN=ArticleExt(id=1242136095731818571, articleId=1242136092724502588, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=环境大气中数据同化技术方法及应用, columnId=1242116902361830275, journalTitle=科技导报, columnName=专题论文, runingTitle=null, highlight=null, articleAbstract=从数据同化的角度，对卡尔曼滤波技术、元启发式算法、贝叶斯推导及逆扩散/轨迹模拟技术、非参数化回归等技术在污染环境大气模拟技术中的应用情况进行了总结分析。分析结果表明，经多种优化方法试用于解决环境监测数据的同化问题中，元启发式算法结合传统优化技术在有效解决环境监测的数据同化问题中具有良好应用前景。, correspAuthors=null, authorNote=徐向军,研究员,研究方向为辐射防护与环境保护,电子信箱:526731224@qq.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=8QOfleFjgZNRze95618dCw==, pdfFileSize=1585555, 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=中国辐射防护研究院, 太原 030006, fund=国际（地区）合作与交流项目（61520106008）；国家自然科学基金优秀青年科学基金项目（61522307）, authors=徐向军, 姚仁太, 陈龙泉, authorsList=徐向军, 姚仁太, 陈龙泉)}, authors=null, 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