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dc.contributor.authorCeballes-Serrano C.C.
dc.contributor.authorGarcia-Lopez S.
dc.contributor.authorJaramillo-Garzon J.A.
dc.contributor.authorCastellanos-Dominguez G.
dc.date.accessioned2020-08-28T22:29:17Z
dc.date.available2020-08-28T22:29:17Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/20.500.12622/3881
dc.description.abstractCurrently, there is a number of tools which allow analyzing information-based behavioral patterns; in the specific case of this article, the analysis of tendencies will be highlighted not only as a tool to predict the behavior of prices in order to measure and process financial market information but also, in a wider standpoint, to take tendencies as a tool to analyze the behavior of certain elements within a specific environment and period of time. Accordingly, the article is intended to set the theoretical, conceptual, and contextual basis necessary to perform the analysis of tendencies through the combination of a monitoring system and an observatory intended to organize, quantify, process, and use information as an indispensable element to implement innovation in the business fieldeng
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84870708211&doi=10.1109%2fSTSIVA.2012.6340585&partnerID=40&md5=fc92e5720d98c3ecc3ca78c2b4762706
dc.titleA strategy for classifying imbalanced data sets based on particle swarm optimizationspa
dc.title.alternativeSTSIVA 2012 - 17th Symposium of Image, Signal Processing, and Artificial Vision
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.rights.accessrightsinfo:eu-repo/semantics/closedAccess
dc.identifier.doi10.1109/STSIVA.2012.6340585
dc.description.edition6340585
dc.relation.citationstartpage218
dc.relation.citationendpage222
dc.type.versioninfo:eu-repo/semantics/publishedVersion


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