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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/71234
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dc.contributor.authorSerapião, Adriane B. S.-
dc.contributor.authorMendes, José Ricardo P.-
dc.date.accessioned2014-05-27T11:24:02Z-
dc.date.accessioned2016-10-25T18:27:37Z-
dc.date.available2014-05-27T11:24:02Z-
dc.date.available2016-10-25T18:27:37Z-
dc.date.issued2009-11-09-
dc.identifierhttp://dx.doi.org/10.1007/978-3-642-02568-6_31-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 5579 LNAI, p. 301-310.-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/11449/71234-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/71234-
dc.description.abstractThis paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.en
dc.format.extent301-310-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectBio-inspired-
dc.subjectColony algorithms-
dc.subjectData sets-
dc.subjectDecision-tree algorithm-
dc.subjectHybrid particles-
dc.subjectRule induction-
dc.subjectData mining-
dc.subjectDecision trees-
dc.subjectIntelligent systems-
dc.subjectMud logging-
dc.subjectOil wells-
dc.subjectPetroleum industry-
dc.subjectWell drilling-
dc.titleClassification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithmen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)-
dc.description.affiliationUNESP/IGCE/DEMAC, C.P. 178, Rio Claro (SP) CEP 13506-900-
dc.description.affiliationUNICAMP/FEM/DEP, C.P. 6122, Campinas (SP) CEP 13081-970-
dc.description.affiliationUnespUNESP/IGCE/DEMAC, C.P. 178, Rio Claro (SP) CEP 13506-900-
dc.identifier.doi10.1007/978-3-642-02568-6_31-
dc.identifier.wosWOS:000269972300031-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.identifier.scopus2-s2.0-70350633099-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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