{"id":"https://openalex.org/W7147743360","doi":"https://doi.org/10.3837/tiis.2026.03.011","title":"GAN-Transformer for Multivariate Power Consumption Imputation","display_name":"GAN-Transformer for Multivariate Power Consumption Imputation","publication_year":2026,"publication_date":"2026-03-31","ids":{"openalex":"https://openalex.org/W7147743360","doi":"https://doi.org/10.3837/tiis.2026.03.011"},"language":null,"primary_location":{"id":"doi:10.3837/tiis.2026.03.011","is_oa":true,"landing_page_url":"https://doi.org/10.3837/tiis.2026.03.011","pdf_url":"https://itiis.org/digital-library/manuscript/file/106120/TIIS Vol 20, No 3-11.pdf","source":{"id":"https://openalex.org/S204131793","display_name":"KSII Transactions on Internet and Information Systems","issn_l":"1976-7277","issn":["1976-7277","2288-1468"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4323966148","host_organization_name":"Korea Society of Internet Information","host_organization_lineage":["https://openalex.org/P4323966148"],"host_organization_lineage_names":["Korea Society of Internet Information"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"KSII Transactions on Internet and Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://itiis.org/digital-library/manuscript/file/106120/TIIS Vol 20, No 3-11.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075403444","display_name":"Huichao Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huichao Kong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132633363","display_name":"Xiaoxia Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoxia Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101554070","display_name":"Haojun Li","orcid":"https://orcid.org/0000-0003-0503-4050"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haojun Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051667091","display_name":"Yake Xiao","orcid":"https://orcid.org/0000-0001-6365-9783"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yake Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132555724","display_name":"Siqi Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siqi Ye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132698400","display_name":"Changwei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Changwei Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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":0.44207234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13429","display_name":"Electricity Theft Detection Techniques","score":0.4007999897003174,"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":0.4007999897003174,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.2232999950647354,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.042500000447034836,"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/imputation","display_name":"Imputation (statistics)","score":0.76910001039505},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7497000098228455},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6891999840736389},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5092999935150146},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.506600022315979},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.46810001134872437},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4643999934196472},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4643999934196472},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.42289999127388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8428999781608582},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.76910001039505},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7497000098228455},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6891999840736389},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5092999935150146},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.506600022315979},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49970000982284546},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4643999934196472},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4643999934196472},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.421099990606308},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.4099000096321106},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3625999987125397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33090001344680786},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.29019999504089355},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.2572000026702881},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3837/tiis.2026.03.011","is_oa":true,"landing_page_url":"https://doi.org/10.3837/tiis.2026.03.011","pdf_url":"https://itiis.org/digital-library/manuscript/file/106120/TIIS Vol 20, No 3-11.pdf","source":{"id":"https://openalex.org/S204131793","display_name":"KSII Transactions on Internet and Information Systems","issn_l":"1976-7277","issn":["1976-7277","2288-1468"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4323966148","host_organization_name":"Korea Society of Internet Information","host_organization_lineage":["https://openalex.org/P4323966148"],"host_organization_lineage_names":["Korea Society of Internet Information"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"KSII Transactions on Internet and Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3837/tiis.2026.03.011","is_oa":true,"landing_page_url":"https://doi.org/10.3837/tiis.2026.03.011","pdf_url":"https://itiis.org/digital-library/manuscript/file/106120/TIIS Vol 20, No 3-11.pdf","source":{"id":"https://openalex.org/S204131793","display_name":"KSII Transactions on Internet and Information Systems","issn_l":"1976-7277","issn":["1976-7277","2288-1468"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4323966148","host_organization_name":"Korea Society of Internet Information","host_organization_lineage":["https://openalex.org/P4323966148"],"host_organization_lineage_names":["Korea Society of Internet Information"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"KSII Transactions on Internet and Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.48726651072502136}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7147743360.pdf","grobid_xml":"https://content.openalex.org/works/W7147743360.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"imputation":[1,32,164],"of":[2,117,127],"missing":[3,132,151],"data":[4,103,163],"in":[5,94],"multivariate":[6],"time":[7],"series":[8],"is":[9],"critical":[10],"for":[11,160],"reliable":[12],"smart":[13],"meter":[14],"analytics":[15],"and":[16,23,48,62,69,119,137,141,146,157],"downstream":[17],"tasks":[18],"such":[19],"as":[20],"demand":[21],"forecasting":[22],"anomaly":[24],"detection.In":[25],"this":[26],"paper,":[27],"we":[28],"propose":[29],"a":[30,53,86,130,155],"novel":[31],"framework":[33],"that":[34,105],"integrates":[35],"generative":[36],"adversarial":[37,83],"networks":[38],"(GANs)":[39],"with":[40,58],"Transformer":[41,55],"encoders":[42],"to":[43,65,78,90],"jointly":[44],"model":[45,109],"temporal":[46,87],"dynamics":[47],"feature":[49],"correlations.The":[50],"generator":[51,77],"employs":[52],"multi-layer":[54],"encoder":[56],"equipped":[57],"sinusoidal":[59],"positional":[60],"encoding":[61],"inter-feature":[63],"attention":[64],"capture":[66],"both":[67,144],"sequential":[68],"crosssensor":[70],"dependencies.A":[71],"lightweight":[72],"Transformer-based":[73],"discriminator":[74],"guides":[75],"the":[76,95,106],"produce":[79],"realistic":[80],"imputations":[81],"through":[82],"learning.We":[84],"introduce":[85],"consistency":[88],"loss":[89],"enforce":[91],"smooth":[92],"transitions":[93],"imputed":[96],"sequences.Extensive":[97],"experiments":[98],"on":[99],"real-world":[100],"electricity":[101],"consumption":[102],"demonstrate":[104],"proposed":[107],"GAN-Transformer":[108],"achieves":[110],"an":[111,120],"average":[112],"mean":[113],"relative":[114],"error":[115,124],"(MRE)":[116],"0.11":[118],"accuracy":[121],"within":[122],"20%":[123],"tolerance":[125],"(ACC@0.2)":[126],"87%":[128],"at":[129],"50%":[131],"rate,":[133],"demonstrating":[134],"superior":[135],"robustness":[136],"visually":[138],"coherent":[139],"reconstructions,":[140],"significantly":[142],"outperforms":[143],"GANonly":[145],"Transformer-only":[147],"baselines":[148],"across":[149],"various":[150],"rates,":[152],"thus":[153],"offers":[154],"scalable":[156],"domain-adaptive":[158],"solution":[159],"practical":[161],"power":[162],"scenarios.":[165]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-02T00:00:00"}