Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble
Identifieur interne : 001A34 ( Istex/Corpus ); précédent : 001A33; suivant : 001A35Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble
Auteurs : Jiansheng Wu ; Long Jin ; Mingzhe LiuSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
Abstract
Abstract: In this paper a novel optimization approach is presented. Network architecture and connection weights of neural networks (NN) are evolved by a particle swarm optimization (PSO) method, and then the appropriate network architecture and connection weights are fed into back-propagation (BP) networks. The ensemble strategy is carried out by simple averaging. The applied example is built with monthly mean rainfall of the whole area in Guangxi, China. The results show that the proposed approach can effectively improves convergence speed and generalization ability of NN.
Url:
DOI: 10.1007/11760191_175
Links to Exploration step
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<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble</title><author><name sortKey="Wu, Jiansheng" sort="Wu, Jiansheng" uniqKey="Wu J" first="Jiansheng" last="Wu">Jiansheng Wu</name><affiliation><mods:affiliation>Department of Mathematics and Computer, Liuzhou Teachers College, Guangxi, China</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: wjsh2002168@163.com</mods:affiliation></affiliation></author><author><name sortKey="Jin, Long" sort="Jin, Long" uniqKey="Jin L" first="Long" last="Jin">Long Jin</name><affiliation><mods:affiliation>Guangxi Research Institute of Meteorological Disaster Mitigation, Nanning, Guangxi, China</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: Jinlong01@163.com</mods:affiliation></affiliation></author><author><name sortKey="Liu, Mingzhe" sort="Liu, Mingzhe" uniqKey="Liu M" first="Mingzhe" last="Liu">Mingzhe Liu</name><affiliation><mods:affiliation>Institutes of Information Sciences and Technology, Massey University, Private Bag 11222, Palmerston North, New Zealand</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: m.z.liu@massey.ac.nz</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:25111D1744C2EBE1284B61782BE0A909511DC5CD</idno><date when="2006" year="2006">2006</date><idno type="doi">10.1007/11760191_175</idno><idno type="url">https://api.istex.fr/document/25111D1744C2EBE1284B61782BE0A909511DC5CD/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">001A34</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble</title><author><name sortKey="Wu, Jiansheng" sort="Wu, Jiansheng" uniqKey="Wu J" first="Jiansheng" last="Wu">Jiansheng Wu</name><affiliation><mods:affiliation>Department of Mathematics and Computer, Liuzhou Teachers College, Guangxi, China</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: wjsh2002168@163.com</mods:affiliation></affiliation></author><author><name sortKey="Jin, Long" sort="Jin, Long" uniqKey="Jin L" first="Long" last="Jin">Long Jin</name><affiliation><mods:affiliation>Guangxi Research Institute of Meteorological Disaster Mitigation, Nanning, Guangxi, China</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: Jinlong01@163.com</mods:affiliation></affiliation></author><author><name sortKey="Liu, Mingzhe" sort="Liu, Mingzhe" uniqKey="Liu M" first="Mingzhe" last="Liu">Mingzhe Liu</name><affiliation><mods:affiliation>Institutes of Information Sciences and Technology, Massey University, Private Bag 11222, Palmerston North, New Zealand</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: m.z.liu@massey.ac.nz</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2006</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">25111D1744C2EBE1284B61782BE0A909511DC5CD</idno><idno type="DOI">10.1007/11760191_175</idno><idno type="ChapterID">175</idno><idno type="ChapterID">Chap175</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: In this paper a novel optimization approach is presented. 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Zurada</name><affiliations><json:string>Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A</json:string><json:string>E-mail: j.zurada@ieee.org</json:string></affiliations></json:item><json:item><name>Bao-Liang Lu</name><affiliations><json:string>Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China</json:string><json:string>E-mail: bllu@sjtu.edu.cn</json:string></affiliations></json:item><json:item><name>Hujun Yin</name><affiliations><json:string>School of Electrical and Electronic Engineering, University of Manchester, UK</json:string><json:string>E-mail: h.yin@manchester.ac.uk</json:string></affiliations></json:item></editor><subject><json:item><value>Computer Science</value></json:item><json:item><value>Computer Science</value></json:item><json:item><value>Computation by Abstract Devices</value></json:item><json:item><value>Computer Communication Networks</value></json:item><json:item><value>Algorithm Analysis and Problem Complexity</value></json:item><json:item><value>Discrete Mathematics in Computer Science</value></json:item><json:item><value>Artificial Intelligence (incl. 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University</OrgName><OrgAddress><City>Pittsburgh</City><State>PA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff3"><OrgName>University of Surrey</OrgName><OrgAddress><City>Guildford</City><Country>UK</Country></OrgAddress></Affiliation><Affiliation ID="Aff4"><OrgName>Cornell University</OrgName><OrgAddress><City>Ithaca</City><State>NY</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff5"><OrgName>ETH Zurich</OrgName><OrgAddress><Country>Switzerland</Country></OrgAddress></Affiliation><Affiliation ID="Aff6"><OrgName>Stanford University</OrgName><OrgAddress><City>CA</City><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff7"><OrgName>Weizmann Institute of Science</OrgName><OrgAddress><City>Rehovot</City><Country>Israel</Country></OrgAddress></Affiliation><Affiliation ID="Aff8"><OrgName>University of Bern</OrgName><OrgAddress><Country>Switzerland</Country></OrgAddress></Affiliation><Affiliation ID="Aff9"><OrgName>Indian Institute of Technology</OrgName><OrgAddress><City>Madras</City><Country>India</Country></OrgAddress></Affiliation><Affiliation ID="Aff10"><OrgName>University of Dortmund</OrgName><OrgAddress><Country>Germany</Country></OrgAddress></Affiliation><Affiliation ID="Aff11"><OrgName>Massachusetts Institute of Technology</OrgName><OrgAddress><City>MA</City><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff12"><OrgName>University of California</OrgName><OrgAddress><City>Los Angeles</City><State>CA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff13"><OrgName>University of California</OrgName><OrgAddress><City>Berkeley</City><State>CA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff14"><OrgName>Rice University</OrgName><OrgAddress><City>Houston</City><State>TX</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff15"><OrgName>Max-Planck Institute of Computer Science</OrgName><OrgAddress><City>Saarbruecken</City><Country>Germany</Country></OrgAddress></Affiliation></EditorGroup></SeriesHeader><Book Language="En"><BookInfo BookProductType="Proceedings" ContainsESM="No" Language="En" MediaType="eBook" NumberingDepth="2" NumberingStyle="ContentOnly" OutputMedium="All" TocLevels="0"><BookID>978-3-540-34483-4</BookID><BookTitle>Advances in Neural Networks - ISNN 2006</BookTitle><BookSubTitle>Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part III</BookSubTitle><BookVolumeNumber>3973</BookVolumeNumber><BookSequenceNumber>3973</BookSequenceNumber><BookDOI>10.1007/11760191</BookDOI><BookTitleID>139139</BookTitleID><BookPrintISBN>978-3-540-34482-7</BookPrintISBN><BookElectronicISBN>978-3-540-34483-4</BookElectronicISBN><BookChapterCount>200</BookChapterCount><BookCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2006</CopyrightYear></BookCopyright><BookSubjectGroup><BookSubject Code="I" Type="Primary">Computer Science</BookSubject><BookSubject Code="I16013" Priority="1" Type="Secondary">Computation by Abstract Devices</BookSubject><BookSubject Code="I13022" Priority="2" Type="Secondary">Computer Communication Networks</BookSubject><BookSubject Code="I16021" Priority="3" Type="Secondary">Algorithm Analysis and Problem Complexity</BookSubject><BookSubject Code="I17028" Priority="4" Type="Secondary">Discrete Mathematics in Computer Science</BookSubject><BookSubject Code="I21017" Priority="5" Type="Secondary">Artificial Intelligence (incl. Robotics)</BookSubject><BookSubject Code="I2203X" Priority="6" Type="Secondary">Pattern Recognition</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup><BookContext><SeriesID>558</SeriesID></BookContext></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff16"><EditorName DisplayOrder="Western"><GivenName>Jun</GivenName><FamilyName>Wang</FamilyName></EditorName><Contact><Email>jwang@mae.cuhk.edu.hk</Email></Contact></Editor><Editor AffiliationIDS="Aff17"><EditorName DisplayOrder="Western"><GivenName>Zhang</GivenName><FamilyName>Yi</FamilyName></EditorName><Contact><Email>zhangyi@uestc.edu.cn</Email></Contact></Editor><Editor AffiliationIDS="Aff18"><EditorName DisplayOrder="Western"><GivenName>Jacek</GivenName><GivenName>M.</GivenName><FamilyName>Zurada</FamilyName></EditorName><Contact><Email>j.zurada@ieee.org</Email></Contact></Editor><Editor AffiliationIDS="Aff19"><EditorName DisplayOrder="Western"><GivenName>Bao-Liang</GivenName><FamilyName>Lu</FamilyName></EditorName><Contact><Email>bllu@sjtu.edu.cn</Email></Contact></Editor><Editor AffiliationIDS="Aff20"><EditorName DisplayOrder="Western"><GivenName>Hujun</GivenName><FamilyName>Yin</FamilyName></EditorName><Contact><Email>h.yin@manchester.ac.uk</Email></Contact></Editor><Affiliation ID="Aff16"><OrgDivision>Department of Mechanical and Automation Engineering</OrgDivision><OrgName>The Chinese University of Hong Kong, Shatin, New Territories</OrgName><OrgAddress><City>Hong Kong</City><Country>China</Country></OrgAddress></Affiliation><Affiliation ID="Aff17"><OrgDivision>Computational Intelligence Laboratory, School of Computer Science and Engineering</OrgDivision><OrgName>University of Electronic Science and Technology of China</OrgName><OrgAddress><Postcode>610054</Postcode><City>Chengdu</City><Country>P.R. China</Country></OrgAddress></Affiliation><Affiliation ID="Aff18"><OrgDivision>Department of Electrical Engineering</OrgDivision><OrgName>University of Louisville</OrgName><OrgAddress><Postcode>40292</Postcode><City>Louisville</City><State>KY</State><Country>U.S.A</Country></OrgAddress></Affiliation><Affiliation ID="Aff19"><OrgDivision>Laboratory for Computational Biology</OrgDivision><OrgName>Shanghai Center for Systems Biomedicine</OrgName><OrgAddress><Street>800 Dong Chuan Rd</Street><Postcode>200240</Postcode><City>Shanghai</City><Country>China</Country></OrgAddress></Affiliation><Affiliation ID="Aff20"><OrgDivision>School of Electrical and Electronic Engineering</OrgDivision><OrgName>University of Manchester</OrgName><OrgAddress><Country>UK</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part10"><PartInfo TocLevels="0"><PartID>10</PartID><PartSequenceNumber>10</PartSequenceNumber><PartTitle>Other Applications</PartTitle><PartChapterCount>24</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>Advances in Neural Networks - ISNN 2006</BookTitle></PartContext></PartInfo><Chapter ID="Chap175" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingDepth="2" NumberingStyle="ContentOnly" TocLevels="0"><ChapterID>175</ChapterID><ChapterDOI>10.1007/11760191_175</ChapterDOI><ChapterSequenceNumber>175</ChapterSequenceNumber><ChapterTitle Language="En">Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble</ChapterTitle><ChapterFirstPage>1202</ChapterFirstPage><ChapterLastPage>1209</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2006</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>10</PartID><BookID>978-3-540-34483-4</BookID><BookTitle>Advances in Neural Networks - ISNN 2006</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff21"><AuthorName DisplayOrder="Western"><GivenName>Jiansheng</GivenName><FamilyName>Wu</FamilyName></AuthorName><Contact><Email>wjsh2002168@163.com</Email></Contact></Author><Author AffiliationIDS="Aff22"><AuthorName DisplayOrder="Western"><GivenName>Long</GivenName><FamilyName>Jin</FamilyName></AuthorName><Contact><Email>Jinlong01@163.com</Email></Contact></Author><Author AffiliationIDS="Aff23"><AuthorName DisplayOrder="Western"><GivenName>Mingzhe</GivenName><FamilyName>Liu</FamilyName></AuthorName><Contact><Email>m.z.liu@massey.ac.nz</Email></Contact></Author><Affiliation ID="Aff21"><OrgDivision>Department of Mathematics and Computer</OrgDivision><OrgName>Liuzhou Teachers College</OrgName><OrgAddress><City>Guangxi</City><Country>China</Country></OrgAddress></Affiliation><Affiliation ID="Aff22"><OrgName>Guangxi Research Institute of Meteorological Disaster Mitigation</OrgName><OrgAddress><City>Nanning</City><State>Guangxi</State><Country>China</Country></OrgAddress></Affiliation><Affiliation ID="Aff23"><OrgDivision>Institutes of Information Sciences and Technology</OrgDivision><OrgName>Massey University</OrgName><OrgAddress><Postbox>Private Bag 11222</Postbox><City>Palmerston North</City><Country>New Zealand</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>In this paper a novel optimization approach is presented. Network architecture and connection weights of neural networks (NN) are evolved by a particle swarm optimization (PSO) method, and then the appropriate network architecture and connection weights are fed into back-propagation (BP) networks. The ensemble strategy is carried out by simple averaging. The applied example is built with monthly mean rainfall of the whole area in Guangxi, China. The results show that the proposed approach can effectively improves convergence speed and generalization ability of NN.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble</title></titleInfo><name type="personal"><namePart type="given">Jiansheng</namePart><namePart type="family">Wu</namePart><affiliation>Department of Mathematics and Computer, Liuzhou Teachers College, Guangxi, China</affiliation><affiliation>E-mail: wjsh2002168@163.com</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Long</namePart><namePart type="family">Jin</namePart><affiliation>Guangxi Research Institute of Meteorological Disaster Mitigation, Nanning, Guangxi, China</affiliation><affiliation>E-mail: Jinlong01@163.com</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Mingzhe</namePart><namePart type="family">Liu</namePart><affiliation>Institutes of Information Sciences and Technology, Massey University, Private Bag 11222, Palmerston North, New Zealand</affiliation><affiliation>E-mail: m.z.liu@massey.ac.nz</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2006</dateIssued><copyrightDate encoding="w3cdtf">2006</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: In this paper a novel optimization approach is presented. Network architecture and connection weights of neural networks (NN) are evolved by a particle swarm optimization (PSO) method, and then the appropriate network architecture and connection weights are fed into back-propagation (BP) networks. The ensemble strategy is carried out by simple averaging. The applied example is built with monthly mean rainfall of the whole area in Guangxi, China. The results show that the proposed approach can effectively improves convergence speed and generalization ability of NN.</abstract><relatedItem type="host"><titleInfo><title>Advances in Neural Networks - ISNN 2006</title><subTitle>Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part III</subTitle></titleInfo><name type="personal"><namePart type="given">Jun</namePart><namePart type="family">Wang</namePart><affiliation>Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China</affiliation><affiliation>E-mail: jwang@mae.cuhk.edu.hk</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Zhang</namePart><namePart type="family">Yi</namePart><affiliation>Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China</affiliation><affiliation>E-mail: zhangyi@uestc.edu.cn</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jacek</namePart><namePart type="given">M.</namePart><namePart type="family">Zurada</namePart><affiliation>Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A</affiliation><affiliation>E-mail: j.zurada@ieee.org</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Bao-Liang</namePart><namePart type="family">Lu</namePart><affiliation>Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China</affiliation><affiliation>E-mail: bllu@sjtu.edu.cn</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Hujun</namePart><namePart type="family">Yin</namePart><affiliation>School of Electrical and Electronic Engineering, University of Manchester, UK</affiliation><affiliation>E-mail: h.yin@manchester.ac.uk</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2006</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book Subject Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book Subject Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I16013">Computation by Abstract Devices</topic><topic authority="SpringerSubjectCodes" authorityURI="I13022">Computer Communication Networks</topic><topic authority="SpringerSubjectCodes" authorityURI="I16021">Algorithm Analysis and Problem Complexity</topic><topic authority="SpringerSubjectCodes" authorityURI="I17028">Discrete Mathematics in Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. 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NY, USA</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Friedemann</namePart><namePart type="family">Mattern</namePart><affiliation>ETH Zurich, Switzerland</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">John</namePart><namePart type="given">C.</namePart><namePart type="family">Mitchell</namePart><affiliation>Stanford University, CA, USA</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Moni</namePart><namePart type="family">Naor</namePart><affiliation>Weizmann Institute of Science, Rehovot, Israel</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Oscar</namePart><namePart type="family">Nierstrasz</namePart><affiliation>University of Bern, Switzerland</affiliation><role><roleTerm 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