{"id":"https://openalex.org/W2971121209","doi":"https://doi.org/10.1109/icphm.2019.8819385","title":"A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection","display_name":"A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2971121209","doi":"https://doi.org/10.1109/icphm.2019.8819385","mag":"2971121209"},"language":"en","primary_location":{"id":"doi:10.1109/icphm.2019.8819385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm.2019.8819385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.osti.gov/biblio/1572820","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007096091","display_name":"Baihong Jin","orcid":"https://orcid.org/0000-0003-4130-832X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Baihong Jin","raw_affiliation_strings":["Department of EECS, University of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"Department of EECS, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416074","display_name":"Yuxin Chen","orcid":"https://orcid.org/0000-0001-6265-5529"},"institutions":[{"id":"https://openalex.org/I122411786","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055","country_code":"US","type":"education","lineage":["https://openalex.org/I122411786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxin Chen","raw_affiliation_strings":["Department of Computing & Mathematical Sciences, California Institute of Technology","California Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Department of Computing & Mathematical Sciences, California Institute of Technology","institution_ids":["https://openalex.org/I122411786"]},{"raw_affiliation_string":"California Institute of Technology","institution_ids":["https://openalex.org/I122411786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380723","display_name":"Dan Li","orcid":"https://orcid.org/0000-0002-3787-1673"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Dan Li","raw_affiliation_strings":["Institute of Data Science, National University of Singapore"],"affiliations":[{"raw_affiliation_string":"Institute of Data Science, National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023927229","display_name":"Kameshwar Poolla","orcid":"https://orcid.org/0000-0001-6098-3537"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kameshwar Poolla","raw_affiliation_strings":["Department of EECS, University of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"Department of EECS, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088660554","display_name":"Alberto Sangiovanni\u2010Vincentelli","orcid":"https://orcid.org/0000-0003-1298-8389"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alberto Sangiovanni-Vincentelli","raw_affiliation_strings":["Department of EECS, University of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"Department of EECS, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007096091"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":2.0216,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.87000618,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9961000084877014,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9562000036239624,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8632187843322754},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6727637052536011},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6679428219795227},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6536370515823364},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6362414360046387},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6212326288223267},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5721130967140198},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5457808375358582},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5377402901649475},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5233361124992371},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4885164499282837},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4642210006713867},{"id":"https://openalex.org/keywords/structured-support-vector-machine","display_name":"Structured support vector machine","score":0.43889111280441284},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4084813594818115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40685415267944336},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14379331469535828},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09957745671272278}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8632187843322754},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6727637052536011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6679428219795227},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6536370515823364},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6362414360046387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6212326288223267},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5721130967140198},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5457808375358582},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5377402901649475},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5233361124992371},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4885164499282837},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4642210006713867},{"id":"https://openalex.org/C125168437","wikidata":"https://www.wikidata.org/wiki/Q7625184","display_name":"Structured support vector machine","level":3,"score":0.43889111280441284},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4084813594818115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40685415267944336},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14379331469535828},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09957745671272278},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icphm.2019.8819385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm.2019.8819385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","raw_type":"proceedings-article"},{"id":"pmh:oai:escholarship.org:ark:/13030/qt32z8r2tv","is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/32z8r2tv","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2019 IEEE International Conference on Prognostics and Health Management Icphm 2019, vol 00","raw_type":"article"},{"id":"pmh:oai:osti.gov:1572820","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/1572820","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:osti.gov:1572820","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/1572820","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2263734637","display_name":null,"funder_award_id":"SinBerBEST","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"},{"id":"https://openalex.org/G2569005740","display_name":null,"funder_award_id":"1645964","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"},{"id":"https://openalex.org/G3034753964","display_name":null,"funder_award_id":"grant","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G5156438236","display_name":null,"funder_award_id":"1645964","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G830009845","display_name":null,"funder_award_id":"Sustain","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1595159159","https://openalex.org/W1879678483","https://openalex.org/W2024060531","https://openalex.org/W2110787940","https://openalex.org/W2123079394","https://openalex.org/W2127979711","https://openalex.org/W2131241448","https://openalex.org/W2132870739","https://openalex.org/W2143662653","https://openalex.org/W2271647922","https://openalex.org/W2468462628","https://openalex.org/W2744067593","https://openalex.org/W2782961382","https://openalex.org/W2970904710","https://openalex.org/W4289146965","https://openalex.org/W6678334688","https://openalex.org/W6678911119","https://openalex.org/W6719982585","https://openalex.org/W6748034048"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W4318559728","https://openalex.org/W3183136280","https://openalex.org/W2775233965","https://openalex.org/W3114716045","https://openalex.org/W4387250752"],"abstract_inverted_index":{"Identifying":[0],"the":[1,67,111,142,146],"change":[2,13,43,68,123],"point":[3,14,124],"of":[4,98,160],"a":[5,12,29,52,79,89,95,105],"system's":[6],"health":[7,72],"status":[8],"is":[9,28,47,149],"important.":[10],"Indeed,":[11],"usually":[15],"signifies":[16],"an":[17],"incipient":[18],"fault":[19],"under":[20],"development.":[21],"The":[22],"One-Class":[23],"Support":[24],"Vector":[25],"Machine":[26],"(OC-SVM)":[27],"popular":[30],"machine":[31],"learning":[32,136],"model":[33,55,148],"for":[34,41,82],"anomaly":[35],"detection":[36],"that":[37,56,103,115],"could":[38],"be":[39,58,152],"used":[40,59],"identifying":[42],"points;":[44],"however,":[45],"it":[46],"sometimes":[48],"difficult":[49],"to":[50,65,93,133,151],"obtain":[51],"good":[53,96],"OC-SVM":[54,84,116,143],"can":[57,117],"on":[60,110],"sensor":[61],"measurement":[62],"time":[63,126],"series":[64,127],"identify":[66],"points":[69],"in":[70,121,125,155],"system":[71],"status.":[73],"In":[74,138],"this":[75],"paper,":[76],"we":[77],"propose":[78],"novel":[80],"approach":[81,87],"calibrating":[83],"models.":[85],"Our":[86,108],"uses":[88],"heuristic":[90],"search":[91],"method":[92],"find":[94],"set":[97],"input":[99],"data":[100],"and":[101],"hyperparameters":[102],"yield":[104],"well-performing":[106],"model.":[107],"results":[109],"C-MAPSS":[112],"dataset":[113],"demonstrate":[114],"achieve":[118],"satisfactory":[119],"accuracy":[120],"detecting":[122],"with":[128,157],"fewer":[129],"training":[130,161],"data,":[131],"compared":[132],"state-of-the-art":[134],"deep":[135],"approaches.":[137],"our":[139],"case":[140],"study,":[141],"calibrated":[144],"by":[145],"proposed":[147],"shown":[150],"useful":[153],"especially":[154],"scenarios":[156],"limited":[158],"amount":[159],"data.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
