{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:44:07Z","timestamp":1772120647774,"version":"3.50.1"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,8,9]],"date-time":"2021-08-09T00:00:00Z","timestamp":1628467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,8,9]],"date-time":"2021-08-09T00:00:00Z","timestamp":1628467200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,8,9]],"date-time":"2021-08-09T00:00:00Z","timestamp":1628467200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8,9]]},"DOI":"10.1109\/ccta48906.2021.9658806","type":"proceedings-article","created":{"date-parts":[[2022,1,3]],"date-time":"2022-01-03T20:17:48Z","timestamp":1641241068000},"page":"240-246","source":"Crossref","is-referenced-by-count":8,"title":["Machine Learning-based Anomaly Detection for Particle Accelerators"],"prefix":"10.1109","author":[{"given":"Davide","family":"Marcato","sequence":"first","affiliation":[]},{"given":"Giovanni","family":"Arena","sequence":"additional","affiliation":[]},{"given":"Damiano","family":"Bortolato","sequence":"additional","affiliation":[]},{"given":"Fabio","family":"Gelain","sequence":"additional","affiliation":[]},{"given":"Valentina","family":"Martinelli","sequence":"additional","affiliation":[]},{"given":"Enrico","family":"Munaron","sequence":"additional","affiliation":[]},{"given":"Marco","family":"Roetta","sequence":"additional","affiliation":[]},{"given":"Giovanni","family":"Savarese","sequence":"additional","affiliation":[]},{"given":"Gian Antonio","family":"Susto","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","first-page":"678","article-title":"Upgrade of the LLRF Control System at LNL","author":"bortolato","year":"2018","journal-title":"Proc of International Conference on Accelerator and Large Experimental Control Systems (ICALEPCS’17) Barcelona Spain 8-13 October 2017"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btq134"},{"key":"ref12","first-page":"1216","article-title":"The EPICS Software Framework Moves from Controls to Physics","author":"white","year":"2019","journal-title":"Proc 10th International Particle Accelerator Conference (IPAC’19)"},{"key":"ref13","article-title":"Data-driven anomaly recognition for unsupervised model-free fault detection in artificial pancreas","author":"meneghetti","year":"2018","journal-title":"IEEE Transactions on Control Systems Technology"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330748"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/en13123136"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45681-3_2"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/335191.335388"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(03)00003-5"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/1081870.1081891"},{"key":"ref4","article-title":"Introducing big data analysis in a proton therapy facility to reduce technical downtime","volume":"icalepcs2019","author":"carmona","year":"2020","journal-title":"Proceedings of the 17th International Conference on Accelerator and Large Experimental Physics Control Systems"},{"key":"ref3","article-title":"Srf cavity fault classification using machine learning at cebaf","volume":"ipac2019","author":"solopova","year":"2019","journal-title":"Proceedings of the 10th Int Particle Accelerator Conf"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CoASE.2013.6653952"},{"key":"ref5","article-title":"Applying artificial intelligence to accelerators","volume":"ipac2018","author":"scheinker","year":"2018","journal-title":"Proceedings of the 9th Int Particle Accelerator Conf"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ITNT49337.2020.9253296"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-57321-8_8"},{"key":"ref2","first-page":"992","article-title":"An Application of Machine Learning for the Analysis of Temperature Rise on the Production Target in Hadron Experimental Facility at J-PARC","author":"agari","year":"2020","journal-title":"Proc ICALEPCS’19"},{"key":"ref1","first-page":"1066","article-title":"Anomaly detection for cern beam transfer installations using machine learning","author":"dewitte","year":"2019","journal-title":"Proc ICALEPCS’19 JACoW"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/S0168-9002(96)00456-1"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-015-5521-0"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1080\/15376494.2019.1609630"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2133360.2133363"}],"event":{"name":"2021 IEEE Conference on Control Technology and Applications (CCTA)","location":"San Diego, CA, USA","start":{"date-parts":[[2021,8,9]]},"end":{"date-parts":[[2021,8,11]]}},"container-title":["2021 IEEE Conference on Control Technology and Applications (CCTA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9658569\/9658587\/09658806.pdf?arnumber=9658806","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:56:34Z","timestamp":1652201794000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9658806\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,9]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/ccta48906.2021.9658806","relation":{},"subject":[],"published":{"date-parts":[[2021,8,9]]}}}