{"id":"https://openalex.org/W4281391298","doi":"https://doi.org/10.1109/cscwd54268.2022.9776156","title":"A Novel Fault Detection Algorithm Based on the Single Indicator Data","display_name":"A Novel Fault Detection Algorithm Based on the Single Indicator Data","publication_year":2022,"publication_date":"2022-05-04","ids":{"openalex":"https://openalex.org/W4281391298","doi":"https://doi.org/10.1109/cscwd54268.2022.9776156"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd54268.2022.9776156","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd54268.2022.9776156","pdf_url":null,"source":{"id":"https://openalex.org/S4363607909","display_name":"2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","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":null,"display_name":"Yunjian Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjian Huang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101682276","display_name":"Peng Qi","orcid":"https://orcid.org/0000-0003-0390-5449"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Qi","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101997375","display_name":"Yan Sun","orcid":"https://orcid.org/0000-0001-5556-6739"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Sun","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.2076,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.38754307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"8","issue":null,"first_page":"752","last_page":"757"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.9904000163078308,"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/computer-science","display_name":"Computer science","score":0.8543731570243835},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6936509013175964},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5999258160591125},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.4758862257003784},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44233208894729614},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4261877238750458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3611871600151062},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.34427183866500854},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15531805157661438}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8543731570243835},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6936509013175964},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5999258160591125},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.4758862257003784},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44233208894729614},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4261877238750458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3611871600151062},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34427183866500854},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15531805157661438},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd54268.2022.9776156","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd54268.2022.9776156","pdf_url":null,"source":{"id":"https://openalex.org/S4363607909","display_name":"2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4000000059604645,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1969456163","https://openalex.org/W2026453187","https://openalex.org/W2093606067","https://openalex.org/W2134490011","https://openalex.org/W2786827964","https://openalex.org/W2804841412","https://openalex.org/W2944703101","https://openalex.org/W3040857534","https://openalex.org/W3047881323","https://openalex.org/W3106543020","https://openalex.org/W3152030785"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4293226380","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W2078455782"],"abstract_inverted_index":{"With":[0],"the":[1,18,42,67,81,114,126,138,151,162,178,191],"rapid":[2],"development":[3],"of":[4,28,44,70,84,116,129,158,193],"Server":[5,19,71],"Cluster":[6,20],"System":[7],"technologies,":[8],"more":[9,11],"and":[10,13,33,47,62,142,155,165,170,206],"services":[12,29],"tasks":[14],"are":[15,30,147,168],"deployed":[16],"on":[17,136],"Systems.":[21],"Despite":[22],"its":[23],"convenience,":[24],"a":[25,98,132,182],"large":[26],"number":[27],"mixed":[31],"together":[32],"affect":[34],"each":[35],"other,":[36],"which":[37,58,106],"brings":[38],"great":[39,49],"difficulties":[40],"to":[41,65,76,89,109,124,149,172,176,189],"detection":[43,101],"equipment":[45],"fault":[46,100,179,194],"causes":[48],"losses.":[50],"Nowadays,":[51],"artificial":[52],"intelligence":[53],"for":[54,103],"IT":[55],"operations":[56],"(AIOps),":[57],"utilizes":[59],"data":[60,130],"analysis":[61],"machine":[63],"learning":[64],"improve":[66],"operation":[68],"quality":[69],"Clusters,":[72],"has":[73,207],"been":[74],"proposed":[75],"solve":[77],"this":[78,94],"problem.":[79],"However,":[80],"existing":[82],"solutions":[83],"AIOps":[85],"cannot":[86],"be":[87],"applied":[88],"different":[90],"scenarios.":[91],"Therefore,":[92],"in":[93,131],"paper,":[95],"we":[96,118],"propose":[97,120],"novel":[99],"method":[102,123,201],"single":[104],"indicators":[105],"is":[107,187],"adaptive":[108],"various":[110],"scenes.":[111],"To":[112],"enrich":[113],"representation":[115],"data,":[117],"first":[119],"an":[121,173],"interval-volatility-rate":[122],"extract":[125],"context":[127],"features":[128,154,157,164,167],"fixed":[133],"interval.":[134],"Based":[135],"this,":[137],"convolutional":[139],"neural":[140],"network":[141,146,175],"long":[143],"short-term":[144],"memory":[145],"employed":[148],"get":[150],"locally":[152],"spatial":[153,163],"temporal":[156,166],"data.":[159],"After":[160],"that,":[161],"combined":[169],"input":[171],"MLP":[174],"perform":[177],"prediction.":[180],"Additionally,":[181],"k":[183],"\u2212":[184],"\u03c3":[185],"principle":[186],"designed":[188],"promote":[190],"sensitivity":[192],"detection.":[195],"Experimental":[196],"results":[197],"show":[198],"that":[199],"our":[200],"outperforms":[202],"other":[203],"competitive":[204],"models":[205],"better":[208],"scalability.":[209]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
