{"id":"https://openalex.org/W7126376498","doi":"https://doi.org/10.3390/info17020131","title":"A Comparative Analysis of Machine Learning Models for Anomaly Detection in Industrial Smart Meter Time-Series Data","display_name":"A Comparative Analysis of Machine Learning Models for Anomaly Detection in Industrial Smart Meter Time-Series Data","publication_year":2026,"publication_date":"2026-02-01","ids":{"openalex":"https://openalex.org/W7126376498","doi":"https://doi.org/10.3390/info17020131"},"language":"en","primary_location":{"id":"doi:10.3390/info17020131","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17020131","pdf_url":"https://www.mdpi.com/2078-2489/17/2/131/pdf?version=1769939921","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/17/2/131/pdf?version=1769939921","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058603293","display_name":"Gulshat Amirkhanova","orcid":"https://orcid.org/0000-0003-3933-5476"},"institutions":[{"id":"https://openalex.org/I185571130","display_name":"Al-Farabi Kazakh National University","ror":"https://ror.org/03q0vrn42","country_code":"KZ","type":"education","lineage":["https://openalex.org/I185571130"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Gulshat Amirkhanova","raw_affiliation_strings":["Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan"],"raw_orcid":"https://orcid.org/0000-0003-3933-5476","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan","institution_ids":["https://openalex.org/I185571130"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119715009","display_name":"Azim Aidynuly","orcid":null},"institutions":[{"id":"https://openalex.org/I185571130","display_name":"Al-Farabi Kazakh National University","ror":"https://ror.org/03q0vrn42","country_code":"KZ","type":"education","lineage":["https://openalex.org/I185571130"]}],"countries":["KZ"],"is_corresponding":true,"raw_author_name":"Azim Aidynuly","raw_affiliation_strings":["Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan","institution_ids":["https://openalex.org/I185571130"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000708611","display_name":"\u0421\u0430\u043b\u0442\u0430\u043d\u0430\u0442 \u0410\u0434\u0438\u043b\u0436\u0430\u043d\u043e\u0432\u0430","orcid":"https://orcid.org/0000-0003-1768-064X"},"institutions":[{"id":"https://openalex.org/I185571130","display_name":"Al-Farabi Kazakh National University","ror":"https://ror.org/03q0vrn42","country_code":"KZ","type":"education","lineage":["https://openalex.org/I185571130"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Saltanat Adilzhanova","raw_affiliation_strings":["Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan"],"raw_orcid":"https://orcid.org/0000-0003-1768-064X","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan","institution_ids":["https://openalex.org/I185571130"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124522653","display_name":"Yanwei Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanwei Fu","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai 200433, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai 200433, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100001127","display_name":"Baizhanova Dina","orcid":null},"institutions":[{"id":"https://openalex.org/I185571130","display_name":"Al-Farabi Kazakh National University","ror":"https://ror.org/03q0vrn42","country_code":"KZ","type":"education","lineage":["https://openalex.org/I185571130"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Baizhanova Dina","raw_affiliation_strings":["Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan"],"raw_orcid":"https://orcid.org/0000-0002-6109-8174","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan","institution_ids":["https://openalex.org/I185571130"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124554218","display_name":"Onggarbek Alipbeki","orcid":null},"institutions":[{"id":"https://openalex.org/I185571130","display_name":"Al-Farabi Kazakh National University","ror":"https://ror.org/03q0vrn42","country_code":"KZ","type":"education","lineage":["https://openalex.org/I185571130"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Onggarbek Alipbeki","raw_affiliation_strings":["Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan"],"raw_orcid":"https://orcid.org/0000-0001-6205-0490","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Big Data, Faculty of Information Technology and Artificial Intelligence, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan","institution_ids":["https://openalex.org/I185571130"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5119715009"],"corresponding_institution_ids":["https://openalex.org/I185571130"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":3.783,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8887961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"17","issue":"2","first_page":"131","last_page":"131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13429","display_name":"Electricity Theft Detection Techniques","score":0.5767999887466431,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.5767999887466431,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.20329999923706055,"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":0.09210000187158585,"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/anomaly-detection","display_name":"Anomaly detection","score":0.7490000128746033},{"id":"https://openalex.org/keywords/smart-meter","display_name":"Smart meter","score":0.45249998569488525},{"id":"https://openalex.org/keywords/metering-mode","display_name":"Metering mode","score":0.448199987411499},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42910000681877136},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38830000162124634},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3634999990463257},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.36149999499320984},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.3513000011444092},{"id":"https://openalex.org/keywords/metre","display_name":"Metre","score":0.3352000117301941}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7490000128746033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6395999789237976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5756999850273132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5083000063896179},{"id":"https://openalex.org/C2779510800","wikidata":"https://www.wikidata.org/wiki/Q1630602","display_name":"Smart meter","level":3,"score":0.45249998569488525},{"id":"https://openalex.org/C30905978","wikidata":"https://www.wikidata.org/wiki/Q815598","display_name":"Metering mode","level":2,"score":0.448199987411499},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42559999227523804},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C151011524","wikidata":"https://www.wikidata.org/wiki/Q11573","display_name":"Metre","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.3264000117778778},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3206000030040741},{"id":"https://openalex.org/C2984282874","wikidata":"https://www.wikidata.org/wiki/Q10952243","display_name":"Industrial equipment","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.31520000100135803},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C67172668","wikidata":"https://www.wikidata.org/wiki/Q622756","display_name":"Electricity meter","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info17020131","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17020131","pdf_url":"https://www.mdpi.com/2078-2489/17/2/131/pdf?version=1769939921","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4a1f7134dbb948c19bc22066cd401ba1","is_oa":false,"landing_page_url":"https://doaj.org/article/4a1f7134dbb948c19bc22066cd401ba1","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 17, Iss 2, p 131 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info17020131","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17020131","pdf_url":"https://www.mdpi.com/2078-2489/17/2/131/pdf?version=1769939921","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4093036651611328}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7126376498.pdf","grobid_xml":"https://content.openalex.org/works/W7126376498.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,65,89,101,143],"integration":[1],"of":[2,23,45,140,149,162],"Advanced":[3],"Metering":[4],"Infrastructure":[5],"(AMI)":[6],"provides":[7],"high-resolution":[8],"electrical":[9],"data,":[10],"essential":[11],"for":[12,34,168,174],"enhancing":[13],"industrial":[14,163],"efficiency":[15],"and":[16,58,158,171],"monitoring":[17],"equipment":[18],"health.":[19],"However,":[20],"the":[21,32,105,112,117,120,159,166],"utility":[22],"this":[24,99],"data":[25],"is":[26],"frequently":[27],"compromised":[28],"by":[29],"anomalies,":[30],"underscoring":[31],"necessity":[33],"robust,":[35],"automated":[36],"detection":[37],"methodologies.":[38],"This":[39],"study":[40],"benchmarks":[41],"three":[42],"distinct":[43],"categories":[44],"machine":[46],"learning":[47,61],"models:":[48],"a":[49,59,70,79,85],"statistical":[50],"baseline":[51],"(SARIMA),":[52],"an":[53,136],"unsupervised":[54],"classifier":[55],"(Isolation":[56],"Forest),":[57],"deep":[60],"reconstruction":[62],"model":[63,103],"(LSTM-Autoencoder).":[64],"evaluation":[66],"was":[67],"conducted":[68],"using":[69],"multivariate":[71],"dataset":[72],"acquired":[73],"from":[74,131],"bakery":[75],"manufactory":[76],"equipment,":[77],"employing":[78],"synthetic":[80],"anomaly":[81],"injection":[82],"framework":[83],"with":[84],"5%":[86],"contamination":[87],"rate.":[88],"results":[90],"indicate":[91],"significant":[92],"challenges":[93],"in":[94],"accurately":[95],"detecting":[96],"anomalies":[97,157],"within":[98],"dataset.":[100],"SARIMA":[102],"achieved":[104],"highest":[106],"average":[107],"F1-Score":[108],"(0.256),":[109],"slightly":[110],"outperforming":[111],"Isolation":[113],"Forest":[114],"(0.233),":[115],"while":[116],"LSTM-Autoencoder":[118],"performed":[119],"poorest":[121],"(0.110).":[122],"Critically,":[123],"all":[124],"models":[125,151],"exhibited":[126],"extremely":[127],"low":[128],"precision":[129],"(ranging":[130],"0.074":[132],"to":[133,153],"0.204),":[134],"indicating":[135],"unacceptably":[137],"high":[138],"rate":[139],"false":[141],"positives.":[142],"findings":[144],"suggest":[145],"that":[146],"standard":[147],"configurations":[148],"these":[150],"struggle":[152],"differentiate":[154],"between":[155],"true":[156],"inherent":[160],"variability":[161],"operations,":[164],"highlighting":[165],"need":[167],"advanced":[169],"optimization":[170],"feature":[172],"engineering":[173],"practical":[175],"deployment.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-02-02T00:00:00"}
