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dc.contributor.authorMichelena, Álvaro
dc.contributor.authorDíaz-Longueira, Antonio
dc.contributor.authorNovais, Paulo
dc.contributor.authorSimić, Dragan
dc.contributor.authorFontenla-Romero, Óscar
dc.contributor.authorCalvo-Rolle, José Luis
dc.date.accessioned2024-12-18T06:47:39Z
dc.date.available2024-12-18T06:47:39Z
dc.date.issued2025-02-14
dc.identifier.citationÁ. Michelena, A. Díaz-Longueira, P. Novais, D. Simić, Ó. Fontenla-Romero, J.L. Calvo-Rolle, Comparative analysis of unsupervised anomaly detection techniques for heat detection in dairy cattle, Neurocomputing 618 (2025) 129088. https://doi.org/10.1016/j.neucom.2024.129088.es_ES
dc.identifier.issn1872-8286
dc.identifier.urihttp://hdl.handle.net/2183/40540
dc.description.abstract[Abstract] Population growth has increased the demand for meat and dairy products, making livestock, especially cattle, key to meeting this demand. This has led to an increase in herd size, complicating efficient herd management. To meet this challenge, innovative technologies, such as monitoring collars, have been developed to improve individual animal management. This research work evaluates and compares three unsupervised anomaly detection methods to identify estrus in dairy cows from intensive farms, based on daily activity data recorded by a commercial monitoring collar. Data from two different dairy farms have been used and the results have been compared by evaluating the behavior both individually and at herd level. The results obtained show a good performance of the selected techniques in the individual animal models. Thus, this research demonstrates that these techniques can be very useful tools in farm management, providing valuable information, improving productivity and, consequently, increasing the economic performance of the farm.es_ES
dc.description.sponsorshipÁlvaro Michelena’s research was supported by the Spanish Ministry of Universities (https://www.universidades.gob.es/), under the “Formación de Profesorado Universitario” grant with reference FPU21/00932. Antonio Díaz-Longueira’s research was supported by the Xunta de Galicia (Regional Government of Galicia) through grants to Ph.D. (http://gain.xunta.gal), under the “Axudas á etapa predoutoral” grant with reference: ED481A-2023-072. CITIC, as a center accredited for excellence within the Galician University System and a member of the CIGUS Network, receives subsidies from the Department of Education, Science, Universities, and Vocational Training of the Xunta de Galicia. Additionally, it is co-financed by the EU through the FEDER Galicia 2021–27 operational program (Ref. ED431G 2023/01). Xunta de Galicia. Grants for the consolidation and structuring of competitive research units, GPC (ED431B 2023/49).es_ES
dc.description.sponsorshipXunta de Galicia; ED431B 2023/49es_ES
dc.description.sponsorshipXunta de Galicia; ED481A-2023-072es_ES
dc.description.sponsorshipXunta de Galicia; ED481A-2023-072es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MUNI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/FPU21%2F00932/ESes_ES
dc.relation.urihttps://doi.org/10.1016/j.neucom.2024.129088es_ES
dc.rightsAttribution 4.0 International https://creativecommons.org/licenses/by/4.0/es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectCattle behaviores_ES
dc.subjectSmart collarses_ES
dc.subjectDBSCANes_ES
dc.subjectLocal outlier factores_ES
dc.subjectIsolation forestes_ES
dc.titleComparative Analysis of Unsupervised Anomaly Detection Techniques for Heat Detection in Dairy Cattlees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleNeurocomputinges_ES
UDC.volume618es_ES
UDC.issue129088es_ES
UDC.startPage1es_ES
UDC.endPage12es_ES
dc.identifier.doihttps://doi.org/10.1016/j.neucom.2024.129088
UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.departamentoEnxeñaría Industriales_ES
UDC.grupoInvCiencia e Técnica Cibernética (CTC)es_ES
UDC.grupoInvLaboratorio de Investigación e Desenvolvemento en Intelixencia Artificial (LIDIA)es_ES
UDC.institutoCentroCITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicaciónes_ES


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