{"id":"https://openalex.org/W2982288764","doi":"https://doi.org/10.1109/icnp.2019.8888110","title":"Anomaly Noise Filtering with Logistic Regression and a New Method for Time Series Trend Computation for Monitoring Systems","display_name":"Anomaly Noise Filtering with Logistic Regression and a New Method for Time Series Trend Computation for Monitoring Systems","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2982288764","doi":"https://doi.org/10.1109/icnp.2019.8888110","mag":"2982288764"},"language":"en","primary_location":{"id":"doi:10.1109/icnp.2019.8888110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp.2019.8888110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 27th International Conference on Network Protocols (ICNP)","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/A5009455568","display_name":"Qing Gao","orcid":"https://orcid.org/0000-0001-8000-7736"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Qing Gao","raw_affiliation_strings":["ANT FINANCIAL SERVICES GROUP"],"affiliations":[{"raw_affiliation_string":"ANT FINANCIAL SERVICES GROUP","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103205239","display_name":"Limin Zhu","orcid":"https://orcid.org/0000-0003-3194-6731"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Limin Zhu","raw_affiliation_strings":["ANT FINANCIAL SERVICES GROUP"],"affiliations":[{"raw_affiliation_string":"ANT FINANCIAL SERVICES GROUP","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088438299","display_name":"Yuxin Lin","orcid":"https://orcid.org/0000-0003-4375-3515"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuxin Lin","raw_affiliation_strings":["ANT FINANCIAL SERVICES GROUP"],"affiliations":[{"raw_affiliation_string":"ANT FINANCIAL SERVICES GROUP","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100451602","display_name":"Xun Chen","orcid":"https://orcid.org/0000-0002-4922-8116"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xun Chen","raw_affiliation_strings":["ANT FINANCIAL SERVICES GROUP"],"affiliations":[{"raw_affiliation_string":"ANT FINANCIAL SERVICES GROUP","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009455568"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6643777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9966999888420105,"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-detection","display_name":"Anomaly detection","score":0.7586592435836792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7547633647918701},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6218636631965637},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5810611844062805},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5664548873901367},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5626574158668518},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.5598456859588623},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5590154528617859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5515272617340088},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5227349400520325},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.49944519996643066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44303297996520996},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4358607232570648},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40373122692108154},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2578423023223877}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7586592435836792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7547633647918701},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6218636631965637},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5810611844062805},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5664548873901367},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5626574158668518},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.5598456859588623},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5590154528617859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5515272617340088},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5227349400520325},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.49944519996643066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44303297996520996},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4358607232570648},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40373122692108154},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2578423023223877},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnp.2019.8888110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp.2019.8888110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 27th International Conference on Network Protocols (ICNP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1536447791","https://openalex.org/W1968354112","https://openalex.org/W1975257359","https://openalex.org/W1995443851","https://openalex.org/W2108712612","https://openalex.org/W2136504847","https://openalex.org/W2164274563","https://openalex.org/W2551393996","https://openalex.org/W2754051771","https://openalex.org/W2785362611","https://openalex.org/W2963166639","https://openalex.org/W3098957257","https://openalex.org/W6745092361"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1],"has":[2],"always":[3],"been":[4],"a":[5,29,51,75,94,101],"hot":[6],"topic":[7],"in":[8,35,89,97],"signal":[9],"processing":[10],"and":[11,74],"machine":[12],"learning.":[13],"Convolutional":[14],"Neural":[15],"Network":[16],"(CNN)":[17],"is":[18],"an":[19,56],"effective":[20],"technique":[21],"to":[22,41,70],"detect":[23],"anomaly.":[24],"However,":[25],"at":[26,124],"Ant":[27,125],"Financial,":[28],"simple":[30],"CNN":[31],"neglects":[32],"certain":[33],"patterns":[34],"real-world":[36],"data":[37],"that":[38],"may":[39],"lead":[40],"triggering":[42],"of":[43,50,78,93,100,108,116],"false":[44,52,91],"alarms.":[45],"To":[46],"reduce":[47],"the":[48,62,72,87,98,106,109,114],"possibility":[49],"alarm,":[53],"we":[54,67,111],"run":[55],"anomaly":[57],"noise":[58],"filtering":[59],"model":[60,73,84],"after":[61],"CNN.":[63],"In":[64],"this":[65],"paper,":[66,110],"introduce":[68],"techniques":[69],"develop":[71],"new":[76],"method":[77,119],"time":[79,102],"series":[80,103],"trend":[81],"computation.":[82],"The":[83],"helps":[85],"increase":[86],"accuracy":[88],"detecting":[90],"anomalies":[92],"rise-fall":[95],"pattern":[96],"traffic(y-value)":[99],"dataset.":[104],"At":[105],"end":[107],"will":[112],"present":[113],"benchmarks":[115],"using":[117],"our":[118],"on":[120],"real":[121],"online":[122],"systems":[123],"Financial.":[126]},"counts_by_year":[{"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"}