{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T17:27:05Z","timestamp":1778347625455,"version":"3.51.4"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Vicomtech Foundation"},{"DOI":"10.13039\/100013404","name":"Universidad EAFIT","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013404","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3188102","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T19:58:34Z","timestamp":1656964714000},"page":"72024-72036","source":"Crossref","is-referenced-by-count":54,"title":["A Hybrid Machine-Learning Ensemble for Anomaly Detection in Real-Time Industry 4.0 Systems"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9949-8915","authenticated-orcid":false,"given":"David","family":"Velasquez","sequence":"first","affiliation":[{"name":"RID on Information Technologies and Communications Research Group, Universidad EAFIT, Medellín, Colombia"}]},{"given":"Enrique","family":"Perez","sequence":"additional","affiliation":[{"name":"Department of Data Intelligence for Energy and Industrial Processes, Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain"}]},{"given":"Xabier","family":"Oregui","sequence":"additional","affiliation":[{"name":"Department of Data Intelligence for Energy and Industrial Processes, Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0594-7941","authenticated-orcid":false,"given":"Arkaitz","family":"Artetxe","sequence":"additional","affiliation":[{"name":"Department of Data Intelligence for Energy and Industrial Processes, Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain"}]},{"given":"Jorge","family":"Manteca","sequence":"additional","affiliation":[{"name":"Technical Department Direction, Mapner, Astigarraga, Spain"}]},{"given":"Jordi Escayola","family":"Mansilla","sequence":"additional","affiliation":[{"name":"Department of Statistics and Operational Research, Universitat Oberta de Catalunya, Rambla del Poblenou, Barcelona, Spain"}]},{"given":"Mauricio","family":"Toro","sequence":"additional","affiliation":[{"name":"RID on Information Technologies and Communications Research Group, Universidad EAFIT, Medellín, Colombia"}]},{"given":"Mikel","family":"Maiza","sequence":"additional","affiliation":[{"name":"Department of Data Intelligence for Energy and Industrial Processes, Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8062-9332","authenticated-orcid":false,"given":"Basilio","family":"Sierra","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Artificial Intelligence, University of Basque Country (UPV\/EHU), Donostia-San Sebastián, Spain"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.5430\/ijfr.v9n2p90"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/pr5030035"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.07.031"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3381028"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2522968.2522981"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.04.070"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.151"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.12.014"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00068"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2921912"},{"issue":"2","key":"ref11","first-page":"2320","article-title":"A survey on anomaly detection using unsupervised learning techniques","volume":"6","author":"Priyanga","year":"2018","journal-title":"Int. J. Creative Res. Thoughts (IJCRT)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2010.235"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ISCMI.2016.24"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2007.11.008"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2015.08.220"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-011-0502-z"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2009.07.010"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/QRS-C.2018.00075"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/335191.335388"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2014.2350451"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.05.058"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ISCC.2014.6912503"},{"key":"ref24","first-page":"1511","article-title":"Fast anomaly detection for streaming data","volume-title":"Proc. IJCAI Int. Joint Conf. Artif. Intell.","author":"Tan"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2019.106458"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/2133360.2133363"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2523813"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/502512.502529"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788611"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/app10020697"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2379776.2379786"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2005.844158"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/34.667881"},{"key":"ref34","volume-title":"Quality Control Implementation in Manufacturing Companies: Motivating Factors and Challenges","author":"Judi","year":"2011"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/MIPRO.2015.7160458"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3068335"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1162\/089976601750264965"},{"key":"ref38","first-page":"155","article-title":"Uniform object generation for optimizing one-class classifiers","volume":"2","author":"Tax","year":"2002","journal-title":"J. Mach. Learn. Res."},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3390\/app8091468"},{"key":"ref40","volume-title":"Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists","author":"Zheng","year":"2018"},{"key":"ref41","volume-title":"Statistics: Fourth International Student Edition","author":"Freedman","year":"2007"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09813703.pdf?arnumber=9813703","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T05:29:06Z","timestamp":1706765346000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9813703\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3188102","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}