{"id":"https://openalex.org/W4388320609","doi":"https://doi.org/10.1145/3600100.3626633","title":"Enhancing Classification of Energy Meters with Limited Labels using a Semi-Supervised Generative Model","display_name":"Enhancing Classification of Energy Meters with Limited Labels using a Semi-Supervised Generative Model","publication_year":2023,"publication_date":"2023-11-03","ids":{"openalex":"https://openalex.org/W4388320609","doi":"https://doi.org/10.1145/3600100.3626633"},"language":"en","primary_location":{"id":"doi:10.1145/3600100.3626633","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3600100.3626633","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3626633","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3626633","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071874699","display_name":"Chun Fu","orcid":"https://orcid.org/0000-0002-6152-3257"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chun Fu","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-6152-3257","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089050773","display_name":"Hussain Kazmi","orcid":"https://orcid.org/0000-0002-7765-8068"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Hussain Kazmi","raw_affiliation_strings":["KU Leuven, Belgium"],"raw_orcid":"https://orcid.org/0000-0002-7765-8068","affiliations":[{"raw_affiliation_string":"KU Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005453560","display_name":"Mat\u00edas Quintana","orcid":"https://orcid.org/0000-0002-0486-221X"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Matias Quintana","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-0486-221X","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045303713","display_name":"Clayton Miller","orcid":"https://orcid.org/0000-0002-1186-4299"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Clayton Miller","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-1186-4299","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13040881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"450","last_page":"453"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9962999820709229,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9962999820709229,"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":0.9929999709129333,"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/T11954","display_name":"Energy Efficiency and Management","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.742003858089447},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.7296038866043091},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5544405579566956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5531835556030273},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.499453067779541},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4883091449737549},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.48705294728279114},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4803379774093628},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.47114840149879456},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4692775011062622},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.44530361890792847},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.440178781747818},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.41799795627593994},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3510192632675171},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10705676674842834},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07927721738815308}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.742003858089447},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.7296038866043091},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5544405579566956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5531835556030273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.499453067779541},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4883091449737549},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.48705294728279114},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4803379774093628},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.47114840149879456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4692775011062622},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.44530361890792847},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.440178781747818},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.41799795627593994},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3510192632675171},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10705676674842834},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07927721738815308},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3600100.3626633","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3600100.3626633","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3626633","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/744657","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/744657","pdf_url":"https://lirias.kuleuven.be/retrieve/284453d6-b29e-4d02-a507-aa1fb4c008f2","source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys), TURKEY, Istanbul, 15-16 November 2023","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1145/3600100.3626633","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3600100.3626633","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3626633","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388320609.pdf","grobid_xml":"https://content.openalex.org/works/W4388320609.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W3002783982","https://openalex.org/W3041657070","https://openalex.org/W4282977571","https://openalex.org/W4310882134","https://openalex.org/W4313575986","https://openalex.org/W4377121437"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W34092691","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W2943467239","https://openalex.org/W1571801203","https://openalex.org/W101422005","https://openalex.org/W192740413","https://openalex.org/W4300902524","https://openalex.org/W3004135598"],"abstract_inverted_index":{"In":[0],"the":[1,4,31,41,50,62,83,92,144,168,176,184],"energy":[2,28,172],"domain,":[3],"classification":[5,159,177],"of":[6,15,34,52,85,109,139,151,170],"power":[7,38,74,88],"meters":[8,39,75],"has":[9,183],"become":[10],"an":[11,119],"increasingly":[12],"significant":[13],"area":[14],"interest,":[16],"such":[17],"as":[18],"appliance":[19],"identification":[20],"and":[21,26,40,45,81,102,161],"characteristics":[22],"prediction,":[23],"enabling":[24],"targeted":[25],"efficient":[27],"management.":[29],"However,":[30],"limited":[32],"availability":[33],"labeled":[35,110,127],"data":[36,90],"for":[37,54,186],"inconsistencies":[42],"in":[43,155,180,189],"labeling":[44],"naming":[46],"conventions":[47],"have":[48],"constrained":[49],"potential":[51,185],"metadata":[53],"further":[55],"application.":[56],"This":[57,78],"study":[58,153,182],"aims":[59],"to":[60,71,142],"bridge":[61],"gap":[63],"by":[64],"employing":[65],"semi-supervised":[66,103],"Generative":[67],"Adversarial":[68],"Networks":[69],"(SGAN)":[70],"classify":[72],"1805":[73],"distributed":[76],"globally.":[77],"approach":[79],"explores":[80],"assesses":[82],"advantages":[84],"incorporating":[86],"unlabeled":[87,171],"meter":[89,173],"into":[91],"learning":[93],"process.":[94],"A":[95],"comparative":[96],"analysis":[97],"is":[98],"performed":[99],"between":[100],"supervised":[101],"baseline":[104],"models":[105],"using":[106],"different":[107],"proportions":[108],"data.":[111,174],"The":[112,148],"results":[113],"reveal":[114],"that":[115,166],"SGAN":[116],"can":[117],"achieve":[118],"accuracy":[120],"rate":[121],"exceeding":[122],"0.8":[123],"with":[124],"just":[125],"100":[126],"samples,":[128],"whereas":[129],"a":[130,137,157,162],"Two-dimensional":[131],"Convolution":[132],"Neural":[133],"Network":[134],"(2D-CNN)":[135],"requires":[136],"minimum":[138],"300":[140],"samples":[141],"attain":[143],"same":[145],"performance":[146],"level.":[147],"innovative":[149],"contribution":[150],"this":[152,181],"lies":[154],"formulating":[156],"refined":[158],"model":[160],"label":[163],"propagation":[164],"method":[165],"optimizes":[167],"use":[169],"Additionally,":[175],"framework":[178],"established":[179],"expanded":[187],"application":[188],"categorizing":[190],"other":[191],"metadata.":[192]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
