{"id":"https://openalex.org/W4384158227","doi":"https://doi.org/10.1109/aiiot58121.2023.10174320","title":"A Comparative Analysis of Deep Learning Models for Power Quality Disturbance Classification","display_name":"A Comparative Analysis of Deep Learning Models for Power Quality Disturbance Classification","publication_year":2023,"publication_date":"2023-06-07","ids":{"openalex":"https://openalex.org/W4384158227","doi":"https://doi.org/10.1109/aiiot58121.2023.10174320"},"language":"en","primary_location":{"id":"doi:10.1109/aiiot58121.2023.10174320","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiiot58121.2023.10174320","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE World AI IoT Congress (AIIoT)","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/A5033835553","display_name":"Sultan Uddin Khan","orcid":"https://orcid.org/0009-0002-2171-7177"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sultan Uddin Khan","raw_affiliation_strings":["North Carolina A & T State University,Dept. of Electrical Engineering,Greensboro,USA"],"affiliations":[{"raw_affiliation_string":"North Carolina A & T State University,Dept. of Electrical Engineering,Greensboro,USA","institution_ids":["https://openalex.org/I35777872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088956116","display_name":"Mohammed Mynuddin","orcid":"https://orcid.org/0000-0001-7898-5485"},"institutions":[{"id":"https://openalex.org/I39815113","display_name":"Georgia Southern University","ror":"https://ror.org/04agmb972","country_code":"US","type":"education","lineage":["https://openalex.org/I39815113"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammed Mynuddin","raw_affiliation_strings":["Georgia Southern University,Dept. of Electrical Engineering,Statesboro,USA","Dept. of Electrical Engineering, Georgia Southern University, Statesboro, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Southern University,Dept. of Electrical Engineering,Statesboro,USA","institution_ids":["https://openalex.org/I39815113"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Georgia Southern University, Statesboro, USA","institution_ids":["https://openalex.org/I39815113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060561281","display_name":"Dewan Mohammed Abdul Ahad","orcid":null},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dewan Mohammed Abdul Ahad","raw_affiliation_strings":["University of North Carolina at Charlotte,Dept. of Electrical Engineering,Charlotte,USA","Dept. of Electrical Engineering, University of North Carolina at Charlotte, Charlotte, USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Dept. of Electrical Engineering,Charlotte,USA","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, University of North Carolina at Charlotte, Charlotte, USA","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101831593","display_name":"Mohammad Iqbal Hossain","orcid":"https://orcid.org/0009-0006-9549-0621"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Iqbal Hossain","raw_affiliation_strings":["North Carolina A & T State University,Dept. of Electrical Engineering,Greensboro,USA"],"affiliations":[{"raw_affiliation_string":"North Carolina A & T State University,Dept. of Electrical Engineering,Greensboro,USA","institution_ids":["https://openalex.org/I35777872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032934693","display_name":"Md Jahidul Islam","orcid":"https://orcid.org/0000-0002-4057-1743"},"institutions":[{"id":"https://openalex.org/I6026837","display_name":"Tuskegee University","ror":"https://ror.org/0137n4m74","country_code":"US","type":"education","lineage":["https://openalex.org/I6026837"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md Jahidul Islam","raw_affiliation_strings":["Tuskegee University,Dept. of Electrical Engineering,Alabama,USA","Dept. of Electrical Engineering, Tuskegee University, Alabama, USA"],"affiliations":[{"raw_affiliation_string":"Tuskegee University,Dept. of Electrical Engineering,Alabama,USA","institution_ids":["https://openalex.org/I6026837"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Tuskegee University, Alabama, USA","institution_ids":["https://openalex.org/I6026837"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104143003","display_name":"Md Fahad Kabir","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]},{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Md Fahad Kabir","raw_affiliation_strings":["Samsung Electronics America,Dept. of Deployment Engineering,NJ,USA","Dept. of Deployment Engineering, Samsung Electronics America, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Samsung Electronics America,Dept. of Deployment Engineering,NJ,USA","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Dept. of Deployment Engineering, Samsung Electronics America, NJ, USA","institution_ids":["https://openalex.org/I4210101778"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5033835553"],"corresponding_institution_ids":["https://openalex.org/I35777872"],"apc_list":null,"apc_paid":null,"fwci":1.7383,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84615511,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"0317","last_page":"0323"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10573","display_name":"Power Quality and Harmonics","score":0.9997000098228455,"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/T10573","display_name":"Power Quality and Harmonics","score":0.9997000098228455,"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/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.9983999729156494,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6812846064567566},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6507943868637085},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6089435815811157},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5007038116455078},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.4211890995502472},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3364598751068115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3262091875076294},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21337348222732544}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6812846064567566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6507943868637085},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6089435815811157},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5007038116455078},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.4211890995502472},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3364598751068115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3262091875076294},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21337348222732544}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aiiot58121.2023.10174320","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiiot58121.2023.10174320","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE World AI IoT Congress (AIIoT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W569503658","https://openalex.org/W1036112049","https://openalex.org/W1965773165","https://openalex.org/W2117265318","https://openalex.org/W2526251947","https://openalex.org/W2807743563","https://openalex.org/W2920552974","https://openalex.org/W2921521179","https://openalex.org/W2963422046","https://openalex.org/W3039814348","https://openalex.org/W3047145943","https://openalex.org/W3195709372","https://openalex.org/W3200884781","https://openalex.org/W4205749087","https://openalex.org/W4281768053","https://openalex.org/W4307206403","https://openalex.org/W4309228068","https://openalex.org/W4310559323","https://openalex.org/W4310613000","https://openalex.org/W4315694979","https://openalex.org/W4315836272","https://openalex.org/W4320062213","https://openalex.org/W4323798980","https://openalex.org/W4327640767","https://openalex.org/W4362501008","https://openalex.org/W4386952866","https://openalex.org/W6779793405","https://openalex.org/W6856721604"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W4327774331","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0,72,121],"increasing":[1],"integration":[2],"of":[3,52,94,110,123,138,145,159],"digital":[4],"technologies":[5],"and":[6,28,86,105,117,164],"communication":[7],"systems":[8],"into":[9],"conventional":[10],"power":[11,16,26,45,68],"grid":[12,24],"infrastructure":[13],"has":[14],"increased":[15],"quality":[17,69],"disturbances":[18,21,70],"(PQDs).":[19],"These":[20],"can":[22],"harm":[23],"operations,":[25],"equipment,":[27],"end-user":[29],"devices.":[30],"Automated":[31],"PQD":[32,139,154,178],"classification":[33,179],"is":[34],"seen":[35],"as":[36,182],"an":[37],"effective":[38,62,171],"solution":[39],"to":[40,150],"this":[41,190],"problem":[42],"in":[43,136,167,189],"the":[44,50,60,129,133,157,169],"grid.":[46],"This":[47],"paper":[48],"presents":[49],"results":[51,122],"a":[53,91,108,142,183],"comprehensive":[54],"comparative":[55,73,125],"study":[56,148],"that":[57,128],"successfully":[58],"identified":[59],"most":[61,170],"deep":[63,77,152],"learning":[64,78],"method":[65],"for":[66,177,186],"classifying":[67],"(PDQs).":[71],"analysis":[74,126],"involved":[75],"various":[76],"models,":[79],"including":[80,96],"ResNet-18,":[81],"CNN+LSTM,":[82],"ResNet-50,":[83],"LSTM,":[84],"RCNN,":[85],"DNN.":[87],"Our":[88,147,173],"dataset":[89,162],"comprises":[90],"diverse":[92],"set":[93],"PQDs,":[95],"voltage":[97,99],"sags,":[98],"swells,":[100],"harmonics,":[101],"flicker,":[102],"transient":[103],"events,":[104],"more,":[106],"with":[107],"total":[109],"207000":[111],"training":[112],"samples,":[113,116],"23000":[114],"validation":[115],"25000":[118],"testing":[119,143],"samples.":[120],"our":[124],"demonstrated":[127],"ResNet-18":[130],"model":[131,160],"outperformed":[132],"other":[134],"models":[135],"terms":[137],"classification,":[140],"achieving":[141],"accuracy":[144],"99.80%.":[146],"contributes":[149],"understanding":[151],"learning-based":[153],"classifiers,":[155],"emphasizing":[156],"role":[158],"architecture,":[161],"characteristics,":[163],"computational":[165],"requirements":[166],"determining":[168],"approach.":[172],"proposed":[174],"test":[175],"bench":[176],"also":[180],"serves":[181],"valuable":[184],"resource":[185],"future":[187],"research":[188],"domain.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}