{"id":"https://openalex.org/W3112213085","doi":"https://doi.org/10.1109/icps48405.2020.9274779","title":"Incorporating Uncertainty into Unsupervised Machine Learning for Cyber-Physical Systems","display_name":"Incorporating Uncertainty into Unsupervised Machine Learning for Cyber-Physical Systems","publication_year":2020,"publication_date":"2020-06-10","ids":{"openalex":"https://openalex.org/W3112213085","doi":"https://doi.org/10.1109/icps48405.2020.9274779","mag":"3112213085"},"language":"en","primary_location":{"id":"doi:10.1109/icps48405.2020.9274779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icps48405.2020.9274779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013624678","display_name":"Carlo Vos","orcid":null},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Carlo Vos","raw_affiliation_strings":["University of Hamburg, Hamburg, Germany"],"affiliations":[{"raw_affiliation_string":"University of Hamburg, Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019605618","display_name":"Benedikt Eiteneuer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Benedikt Eiteneuer","raw_affiliation_strings":["Lemgo, Germany"],"affiliations":[{"raw_affiliation_string":"Lemgo, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012395966","display_name":"Oliver Niggemann","orcid":"https://orcid.org/0000-0001-8747-3596"},"institutions":[{"id":"https://openalex.org/I190134885","display_name":"Helmut Schmidt University","ror":"https://ror.org/04e8jbs38","country_code":"DE","type":"education","lineage":["https://openalex.org/I190134885"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Oliver Niggemann","raw_affiliation_strings":["Helmut Schmidt University, Hamburg, Germany"],"affiliations":[{"raw_affiliation_string":"Helmut Schmidt University, Hamburg, Germany","institution_ids":["https://openalex.org/I190134885"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013624678"],"corresponding_institution_ids":["https://openalex.org/I159176309"],"apc_list":null,"apc_paid":null,"fwci":0.2942,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57592969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"475","last_page":"480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.721483588218689},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6837540864944458},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6453744173049927},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5936405658721924},{"id":"https://openalex.org/keywords/cyber-physical-system","display_name":"Cyber-physical system","score":0.5920565724372864},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5694124102592468},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5345534086227417},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4486892819404602},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4367409944534302},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.431837797164917},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42710429430007935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.721483588218689},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6837540864944458},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6453744173049927},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5936405658721924},{"id":"https://openalex.org/C179768478","wikidata":"https://www.wikidata.org/wiki/Q1120057","display_name":"Cyber-physical system","level":2,"score":0.5920565724372864},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5694124102592468},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5345534086227417},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4486892819404602},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4367409944534302},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.431837797164917},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42710429430007935},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icps48405.2020.9274779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icps48405.2020.9274779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1537439862","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W2029608738","https://openalex.org/W2115627867","https://openalex.org/W2122646361","https://openalex.org/W2535642622","https://openalex.org/W2557283755","https://openalex.org/W2600383743","https://openalex.org/W2608911009","https://openalex.org/W2751448052","https://openalex.org/W2768775282","https://openalex.org/W2769919275","https://openalex.org/W2797405679","https://openalex.org/W2912644960","https://openalex.org/W3098725059","https://openalex.org/W4242373412","https://openalex.org/W6758821516"],"related_works":["https://openalex.org/W3004173571","https://openalex.org/W2546638913","https://openalex.org/W2209816623","https://openalex.org/W2968885840","https://openalex.org/W2008822734","https://openalex.org/W3135700974","https://openalex.org/W4313307484","https://openalex.org/W2093359968","https://openalex.org/W4385335406","https://openalex.org/W4288388567"],"abstract_inverted_index":{"In":[0,112],"the":[1,7,39,100,109,120,133],"field":[2],"of":[3,10,38,108],"Cyber-Physical":[4],"Systems":[5],"(CPS),":[6],"early":[8],"detection":[9],"anomalies":[11],"is":[12,97,105],"crucial":[13],"to":[14,35,114],"avoid":[15],"future":[16],"faulty":[17],"behaviors,":[18],"e.g.":[19],"preventing":[20],"downtimes":[21],"or":[22],"decreasing":[23],"product":[24],"qualities.":[25],"As":[26],"a":[27],"solution,":[28],"unsupervised":[29],"machine":[30,77],"learning":[31,78],"can":[32],"be":[33,83],"used":[34,126],"learn":[36],"models":[37,81],"historic":[40],"system":[41],"behavior":[42],"and":[43,137],"consequentially":[44],"detect":[45],"deviations":[46],"from":[47],"these":[48],"models.":[49,111],"Since":[50],"CPS":[51],"data":[52],"are":[53,68],"high":[54],"dimensional":[55],"time":[56],"series,":[57],"suitable":[58],"approaches":[59],"such":[60,76,116],"as":[61],"Long":[62],"Short-Term":[63],"Memory":[64],"(LSTM)":[65],"neural":[66],"networks":[67],"good":[69],"solution":[70,134],"candidates.CPSs":[71],"have":[72],"specific":[73],"requirements":[74],"for":[75],"algorithms.":[79],"Learned":[80],"must":[82],"especially":[84],"useful":[85],"in":[86],"closed":[87],"control":[88],"loops,":[89],"i.e.":[90],"without":[91],"human":[92],"supervision.":[93],"For":[94],"this,":[95],"it":[96],"essential":[98],"that":[99],"uncertainty":[101],"about":[102],"model":[103],"predictions":[104],"also":[106,131],"part":[107],"learned":[110],"order":[113],"incorporate":[115],"uncertainties,":[117],"we":[118],"modify":[119],"mean":[121],"squared":[122],"error":[123],"loss":[124],"function":[125],"by":[127],"LSTM.":[128],"This":[129],"paper":[130],"analyses":[132],"on":[135],"artificial":[136],"real":[138],"data.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}