乐胖代购免代理版

{"id":"https://openalex.org/W2782273298","doi":"https://doi.org/10.1109/test.2017.8242043","title":"Changepoint-based anomaly detection in a core router system","display_name":"Changepoint-based anomaly detection in a core router system","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2782273298","doi":"https://doi.org/10.1109/test.2017.8242043","mag":"2782273298"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/test.2017.8242043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5071008842","display_name":"Shi Jin","orcid":"https://orcid.org/0000-0001-9145-3862"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shi Jin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101914137","display_name":"Zhaobo Zhang","orcid":"https://orcid.org/0000-0003-3449-796X"},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaobo Zhang","raw_affiliation_strings":["Huawei Technologies Co. Ltd, San Jose, CA"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co. Ltd, San Jose, CA","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033880864","display_name":"Krishnendu Chakrabarty","orcid":"https://orcid.org/0000-0003-4475-6435"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krishnendu Chakrabarty","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014106133","display_name":"Xinli Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinli Gu","raw_affiliation_strings":["Huawei Technologies Co. Ltd, San Jose, CA"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co. Ltd, San Jose, CA","institution_ids":["https://openalex.org/I4210146936"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.614,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":15,"citation_normalized_percentile":{"value":0.612369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":89},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998,"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":0.9996,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5754366}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7495923},{"id":"https://openalex.org/C2775896111","wikidata":"https://www.wikidata.org/wiki/Q642560","display_name":"Router","level":2,"score":0.6437439},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.60409606},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5754366},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.50178194},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.24944991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2296373},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12580293},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07889253},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/test.2017.8242043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":27,"referenced_works":["https://openalex.org/W1534677927","https://openalex.org/W1558516248","https://openalex.org/W1673310716","https://openalex.org/W1680392829","https://openalex.org/W1975684011","https://openalex.org/W1977838479","https://openalex.org/W2007087405","https://openalex.org/W2036805968","https://openalex.org/W2095157729","https://openalex.org/W2105642232","https://openalex.org/W2117873906","https://openalex.org/W2119821739","https://openalex.org/W2120617515","https://openalex.org/W2122646361","https://openalex.org/W2147388619","https://openalex.org/W2149315881","https://openalex.org/W2183098680","https://openalex.org/W2226245130","https://openalex.org/W2330210193","https://openalex.org/W2542543501","https://openalex.org/W2555211786","https://openalex.org/W2568011300","https://openalex.org/W3208688400","https://openalex.org/W4239510810","https://openalex.org/W4248195866","https://openalex.org/W4249923483","https://openalex.org/W639907764"],"related_works":["https://openalex.org/W4377864969","https://openalex.org/W4300558037","https://openalex.org/W4290647774","https://openalex.org/W3210364259","https://openalex.org/W3207797160","https://openalex.org/W3189286258","https://openalex.org/W3120251014","https://openalex.org/W2912112202","https://openalex.org/W2806741695","https://openalex.org/W2667207928"],"abstract_inverted_index":{"Prognostic":[0],"diagnosis":[1,22],"is":[2,99],"desirable":[3],"for":[4],"commercial":[5,119],"core":[6,120],"router":[7,121],"systems":[8,122],"to":[9,41,79,90,102,125],"ensure":[10],"early":[11],"failure":[12,33],"prediction":[13],"and":[14,74],"fast":[15],"error":[16],"recovery.":[17],"The":[18],"effectiveness":[19],"of":[20,48,61,94,107,118],"prognostic":[21],"depends":[23],"on":[24,85],"whether":[25],"anomalies":[26],"can":[27],"be":[28],"accurately":[29],"detected":[30],"before":[31],"a":[32,62,104,116],"occurs.":[34],"However,":[35],"traditional":[36,143],"anomaly":[37,64,129,137],"detection":[38],"techniques":[39],"fail":[40],"detect":[42,80,91],"\"outliers\"":[43],"when":[44],"the":[45,49,59,127],"statistical":[46],"properties":[47],"monitored":[50],"data":[51],"change":[52],"significantly":[53],"as":[54],"time":[55],"proceeds.":[56],"We":[57],"describe":[58],"design":[60],"changepoint-based":[63,136],"detector":[65,138],"that":[66,134],"first":[67],"detects":[68],"changepoints":[69,78],"from":[70,110,115],"collected":[71,114],"time-series":[72],"data,":[73],"then":[75,100],"utilizes":[76],"these":[77],"anomalies.":[81],"Two":[82],"approaches":[83],"based":[84],"maximum-likelihood":[86],"estimation":[87],"are":[88,123],"implemented":[89],"different":[92],"types":[93],"changepoints.":[95],"A":[96],"clustering":[97],"method":[98],"developed":[101],"identify":[103],"wide":[105],"range":[106],"normal/abnormal":[108],"patterns":[109],"changepoint":[111],"windows.":[112],"Data":[113],"set":[117],"used":[124],"validate":[126],"proposed":[128],"detector.":[130],"Experimental":[131],"results":[132],"show":[133],"our":[135],"achieves":[139],"better":[140],"performance":[141],"than":[142],"methods.":[144]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2782273298","counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4}],"updated_date":"2025-01-19T18:15:21.935383","created_date":"2018-01-12"}