Please use this identifier to cite or link to this item: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1724
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dc.contributor31249es_ES
dc.contributor.otherhttps://orcid.org/0000-0002-7337-8974-
dc.coverage.spatialGlobales_ES
dc.creatorRobles Guerrero, Antonio-
dc.creatorSaucedo Anaya, Tonatiuh-
dc.creatorGonzález Ramírez, Efrén-
dc.creatorDe la Rosa Vargas, José Ismael-
dc.date.accessioned2020-04-17T19:50:38Z-
dc.date.available2020-04-17T19:50:38Z-
dc.date.issued2019-04-
dc.identifierinfo:eu-repo/semantics/publishedVersiones_ES
dc.identifier.issn0168-1699es_ES
dc.identifier.urihttp://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1724-
dc.identifier.urihttps://doi.org/10.48779/1ff9-je35-
dc.description.abstractThis study presents an analysis of a multiclass classification problem to identify queenless states by monitoring bee sound in two possible cases; a strong and healthy colony that lost its queen and a reduced population queenless colony. The sound patterns were compared with patterns of healthy queenright colonies. Five colonies of Carniola honey bee were monitored by using a system based on a Raspberry Pi 2 and omnidirectional microphones placed inside the hives. Feature extraction was carried out by Mel Frequency Cepstral Coefficients (MFCCs) method. A multiclass model with three outcome variables was constructed. For feature selection and regularization, a Lasso logistic Regression model was used along with one vs all strategy. To provide visual evidence and examine the results, data was analyzed by scatter plots of Singular Value Decomposition (SVD). The results show that is possible to detect the queenless state in both cases. Queenless or healthy colonies can generate slightly different patterns and the data clusters of the same condition tend to be close. The proposed methodology can be applied for the analysis of more conditions in bee colonies.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationhttps://doi.org/10.1016/j.compag.2019.02.024es_ES
dc.relation.urigeneralPublices_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourceComputers and Electronics in Agriculture, Vol. 159, abril de 2019, pp. 69-74es_ES
dc.subject.classificationINGENIERIA Y TECNOLOGIA [7]es_ES
dc.subject.otherQueenless statees_ES
dc.subject.otherBeehive monitoringes_ES
dc.subject.otherBee soundes_ES
dc.subject.otherSound analysises_ES
dc.titleAnalysis of a multiclass classification problem by Lasso Logistic Regression and Singular Value Decomposition to identify sound patterns in queenless bee colonieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
Appears in Collections:*Documentos Académicos*-- M. en Ciencias del Proc. de la Info.

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