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A comparison of multivariate time series clustering methods

dc.contributor.authorVázquez, Iago
dc.contributor.authorVillar Flecha, José Ramón 
dc.contributor.authorSedano, Javier
dc.contributor.authorSimić, Svetlana
dc.date.accessioned2021-02-19T13:24:50Z
dc.date.available2021-02-19T13:24:50Z
dc.date.issued2021
dc.identifier.citationVázquez I., Villar J.R., Sedano J., Simić S. (2021) A comparison of multivariate time series clustering methods. En: Herrero Á., Cambra C., Urda D., Sedano J., Quintián H., Corchado E. (eds) 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020). SOCO 2020
dc.identifier.isbn978-3-030-57801-5
dc.identifier.urihttp://hdl.handle.net/10651/57982
dc.descriptionInternational Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO) (15th. 2020. Burgos, Spain)
dc.description.sponsorshipThis research has been funded partially by Spanish Ministry of Economy, Industry and Competitiveness (MINECO) under grant TIN2017-84804-R and by Foundation for the Promotion of Applied Scientific Research and Technology in Asturias, under grant FC-GRUPIN-IDI2018000226.spa
dc.format.extentp. 571-579spa
dc.language.isoengspa
dc.publisherSpringerspa
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computing;1268
dc.rights© 2021 Springer Nature Switzerland AG. Part of Springer Nature
dc.titleA comparison of multivariate time series clustering methodsspa
dc.typeinfo:eu-repo/semantics/bookPartspa
dc.identifier.doi10.1007/978-3-030-57802-2_55
dc.type.dcmitextspa
dc.relation.projectIDMINECO/TIN2017-84804-Rspa
dc.relation.projectIDFC-GRUPIN-IDI2018000226spa
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-030-57802-2_55


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