{"id":"https://openalex.org/W4364322315","doi":"https://doi.org/10.1109/tim.2023.3265756","title":"A Multidimensional Feature-Driven Ensemble Model for Accurate Classification of Complex Power Quality Disturbance","display_name":"A Multidimensional Feature-Driven Ensemble Model for Accurate Classification of Complex Power Quality Disturbance","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4364322315","doi":"https://doi.org/10.1109/tim.2023.3265756"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3265756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3265756","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5031261618","display_name":"Yulong Liu","orcid":"https://orcid.org/0000-0002-0439-6925"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yulong Liu","raw_affiliation_strings":["College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062250336","display_name":"Ding Yuan","orcid":"https://orcid.org/0000-0002-6925-7862"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Yuan","raw_affiliation_strings":["College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006244653","display_name":"Fan Hongwei","orcid":"https://orcid.org/0000-0002-6717-9768"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Fan","raw_affiliation_strings":["College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038370496","display_name":"Tao Jin","orcid":"https://orcid.org/0000-0003-3829-4545"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Jin","raw_affiliation_strings":["College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061901055","display_name":"Mohamed A. Mohamed","orcid":"https://orcid.org/0000-0001-8700-0270"},"institutions":[{"id":"https://openalex.org/I89466785","display_name":"Minia University","ror":"https://ror.org/02hcv4z63","country_code":"EG","type":"education","lineage":["https://openalex.org/I89466785"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mohamed A. Mohamed","raw_affiliation_strings":["Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt","institution_ids":["https://openalex.org/I89466785"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5031261618"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":4.6047,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.95462534,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10573","display_name":"Power Quality and Harmonics","score":0.9998999834060669,"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":0.9998999834060669,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9958000183105469,"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"}},{"id":"https://openalex.org/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.9937000274658203,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6412839293479919},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5564833879470825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4774475693702698},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47284749150276184},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43843603134155273},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4348873496055603},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.42924734950065613},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41351187229156494},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4122197926044464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3913705050945282},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3734700679779053},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15592294931411743}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6412839293479919},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5564833879470825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4774475693702698},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47284749150276184},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43843603134155273},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4348873496055603},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.42924734950065613},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41351187229156494},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4122197926044464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3913705050945282},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3734700679779053},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15592294931411743},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3265756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3265756","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.5799999833106995,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G3661259006","display_name":null,"funder_award_id":"51977039","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2062936627","https://openalex.org/W2325607671","https://openalex.org/W2345969227","https://openalex.org/W2461851250","https://openalex.org/W2529692997","https://openalex.org/W2547361322","https://openalex.org/W2551310898","https://openalex.org/W2765698362","https://openalex.org/W2769019225","https://openalex.org/W2790023553","https://openalex.org/W2797783267","https://openalex.org/W2890548886","https://openalex.org/W2901358399","https://openalex.org/W2905665596","https://openalex.org/W2911315707","https://openalex.org/W2945767701","https://openalex.org/W2969811671","https://openalex.org/W2992636801","https://openalex.org/W2997360030","https://openalex.org/W3011604333","https://openalex.org/W3022676760","https://openalex.org/W3041986173","https://openalex.org/W3082307413","https://openalex.org/W3110694258","https://openalex.org/W3126027485","https://openalex.org/W3163569297","https://openalex.org/W3205121537","https://openalex.org/W3213042169","https://openalex.org/W3216575363"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4231775656","https://openalex.org/W2611989081","https://openalex.org/W2046435967","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W2383646825","https://openalex.org/W4304166257","https://openalex.org/W2371018915"],"abstract_inverted_index":{"As":[0],"the":[1,12,30,49,58,75,104,112,115,126,133,163,172,191,216,227],"proportion":[2],"of":[3,14,33,52,114,132,151,155,174,229],"power":[4,9,15,204],"electronics-related":[5],"facilities":[6],"in":[7,74,171],"modern":[8],"systems":[10],"increases,":[11],"types":[13,154],"quality":[16],"disturbances":[17],"(PQDs)":[18],"tend":[19],"to":[20,27,110,142,168,221],"become":[21],"more":[22],"complex.":[23],"Traditional":[24],"methods":[25,225],"struggle":[26],"accurately":[28],"perform":[29],"classification":[31,51,130,228],"task":[32],"complex":[34,53,230],"PQDs":[35,156,199],"under":[36,157],"artificial":[37],"empirical":[38],"guidance.":[39],"This":[40],"paper":[41],"proposes":[42],"a":[43,147],"multidimensional":[44,97],"feature-driven":[45],"ensemble":[46],"model":[47,69,137,164,193],"for":[48,96,119,226],"accurate":[50],"PQDs,":[54],"which":[55,123],"can":[56],"complete":[57,111],"self-learning":[59],"function":[60],"from":[61,201,207],"data.":[62],"Unlike":[63],"existing":[64,222],"deep":[65,223],"learning-based":[66,224],"methods,":[67],"this":[68],"considers":[70],"both":[71,208],"spatial":[72],"features":[73,98],"time-frequency":[76],"domain":[77],"and":[78,88,129,183,210],"temporal":[79],"relational":[80],"features.":[81],"Based":[82],"on":[83,146,197],"fully":[84],"convolutional":[85,121],"networks":[86],"(FCN)":[87],"bidirectional":[89],"gated":[90],"recurrent":[91],"unit":[92],"(BiGRU),":[93],"sub-modules":[94],"suitable":[95],"mining":[99],"are":[100],"constructed":[101],"separately.":[102],"Meanwhile,":[103],"squeeze-and-excitation":[105],"network":[106],"(SENet)":[107],"is":[108,219],"introduced":[109],"computation":[113],"channel":[116],"attention":[117],"mechanism":[118],"each":[120],"layer,":[122],"effectively":[124],"improves":[125],"training":[127],"efficiency":[128],"accuracy":[131],"model.":[134],"The":[135],"proposed":[136,192,217],"has":[138,165,194],"been":[139,166,195],"thoroughly":[140],"tested":[141,196],"validate":[143],"its":[144,189],"effectiveness":[145],"synthetic":[148],"dataset":[149],"consisting":[150],"71":[152],"different":[153],"varying":[158],"signal-to-noise":[159],"ratios":[160],"(SNRs).":[161],"Additionally,":[162],"proven":[167],"be":[169],"robust":[170],"face":[173],"external":[175],"factors":[176],"such":[177],"as":[178],"DC":[179],"offset,":[180],"frequency":[181],"variations,":[182],"phase":[184],"jumps.":[185],"To":[186],"further":[187],"demonstrate":[188],"reliability,":[190],"real":[198],"generated":[200],"an":[202],"AC":[203],"source.":[205],"Results":[206],"simulation":[209],"experimentation":[211],"have":[212],"conclusively":[213],"shown":[214],"that":[215],"method":[218],"superior":[220],"PQDs.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
