{"id":"https://openalex.org/W3107912257","doi":"https://doi.org/10.1109/access.2020.3036885","title":"Missing-Insensitive Short-Term Load Forecasting Leveraging Autoencoder and LSTM","display_name":"Missing-Insensitive Short-Term Load Forecasting Leveraging Autoencoder and LSTM","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3107912257","doi":"https://doi.org/10.1109/access.2020.3036885","mag":"3107912257"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3036885","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036885","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252883.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252883.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031984600","display_name":"Kyungnam Park","orcid":"https://orcid.org/0000-0003-2817-2974"},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kyungnam Park","raw_affiliation_strings":["Department of Electronic Engineering, Sogang University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-2817-2974","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Sogang University, Seoul, South Korea","institution_ids":["https://openalex.org/I148751991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067776690","display_name":"Jaeik Jeong","orcid":"https://orcid.org/0000-0002-5796-8106"},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeik Jeong","raw_affiliation_strings":["Department of Electronic Engineering, Sogang University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5796-8106","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Sogang University, Seoul, South Korea","institution_ids":["https://openalex.org/I148751991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048631343","display_name":"Dongjoo Kim","orcid":"https://orcid.org/0000-0002-8924-257X"},"institutions":[{"id":"https://openalex.org/I198972184","display_name":"Korea Electric Power Corporation (South Korea)","ror":"https://ror.org/04fperw70","country_code":"KR","type":"company","lineage":["https://openalex.org/I198972184"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongjoo Kim","raw_affiliation_strings":["Smart Power Distribution Laboratory, Korea Power Electric Corporation (KEPCO) Research Institute, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-8924-257X","affiliations":[{"raw_affiliation_string":"Smart Power Distribution Laboratory, Korea Power Electric Corporation (KEPCO) Research Institute, Daejeon, South Korea","institution_ids":["https://openalex.org/I198972184"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049420521","display_name":"Hongseok Kim","orcid":"https://orcid.org/0000-0002-5744-2358"},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hongseok Kim","raw_affiliation_strings":["Department of Electronic Engineering, Sogang University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5744-2358","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Sogang University, Seoul, South Korea","institution_ids":["https://openalex.org/I148751991"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031984600"],"corresponding_institution_ids":["https://openalex.org/I148751991"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.8723,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.86166215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"206039","last_page":"206048"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9998999834060669,"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/T11052","display_name":"Energy Load and Power Forecasting","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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9327828288078308},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.8196697235107422},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.7539092302322388},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7102551460266113},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6882714033126831},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6146085858345032},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42797282338142395},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4147701561450958},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4144800901412964}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9327828288078308},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8196697235107422},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7539092302322388},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7102551460266113},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6882714033126831},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6146085858345032},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42797282338142395},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4147701561450958},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4144800901412964},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3036885","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036885","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252883.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3af8c82c91304385bf1b87ff7ad0640c","is_oa":true,"landing_page_url":"https://doaj.org/article/3af8c82c91304385bf1b87ff7ad0640c","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 206039-206048 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3036885","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036885","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252883.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5080751969","display_name":null,"funder_award_id":"20192010107290","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G644697155","display_name":null,"funder_award_id":"20192010107290","funder_id":"https://openalex.org/F4320335199","funder_display_name":"Korea Institute of Energy Technology Evaluation and Planning"},{"id":"https://openalex.org/G6767772484","display_name":null,"funder_award_id":"19NSPS-B152996-02","funder_id":"https://openalex.org/F4320324625","funder_display_name":"Korea Agency for Infrastructure Technology Advancement"}],"funders":[{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320324625","display_name":"Korea Agency for Infrastructure Technology Advancement","ror":"https://ror.org/00rxf7n07"},{"id":"https://openalex.org/F4320335199","display_name":"Korea Institute of Energy Technology Evaluation and Planning","ror":"https://ror.org/02zq38y32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3107912257.pdf","grobid_xml":"https://content.openalex.org/works/W3107912257.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1964984358","https://openalex.org/W1985419027","https://openalex.org/W2020798301","https://openalex.org/W2106742347","https://openalex.org/W2402144811","https://openalex.org/W2552991604","https://openalex.org/W2562403923","https://openalex.org/W2570190408","https://openalex.org/W2601171548","https://openalex.org/W2747648188","https://openalex.org/W2783505041","https://openalex.org/W2786361040","https://openalex.org/W2792253101","https://openalex.org/W2799119160","https://openalex.org/W2893532431","https://openalex.org/W2894714913","https://openalex.org/W2897821674","https://openalex.org/W2898718502","https://openalex.org/W2903802301","https://openalex.org/W2907277777","https://openalex.org/W2953384591","https://openalex.org/W2961951330","https://openalex.org/W2962769218","https://openalex.org/W2964066500","https://openalex.org/W2964121744","https://openalex.org/W2969293360","https://openalex.org/W2974046511","https://openalex.org/W2978743137","https://openalex.org/W3001479960","https://openalex.org/W3007665943","https://openalex.org/W4229658977","https://openalex.org/W4297790320","https://openalex.org/W6631190155","https://openalex.org/W6713134421","https://openalex.org/W6718367848","https://openalex.org/W6750820242","https://openalex.org/W6761580696"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"In":[0,41],"most":[1],"deep":[2,24,47],"learning-based":[3],"load":[4,33,56,71],"forecasting,":[5],"an":[6],"intact":[7],"dataset":[8],"is":[9,26],"required.":[10],"Since":[11],"many":[12],"real-world":[13],"datasets":[14],"contain":[15],"missing":[16,21,30,53,120],"values":[17],"for":[18,69,89],"various":[19],"reasons,":[20],"imputation":[22,31,54],"using":[23],"learning":[25,48],"actively":[27],"studied.":[28],"However,":[29],"and":[32,55,82],"forecasting":[34,115],"have":[35],"been":[36],"considered":[37,88],"independently":[38],"so":[39],"far.":[40],"this":[42],"article,":[43],"we":[44],"provide":[45],"a":[46,60],"framework":[49],"that":[50,107],"jointly":[51],"considers":[52],"forecasting.":[57,72],"We":[58],"consider":[59],"family":[61],"of":[62,92,102],"autoencoder/long":[63],"short-term":[64],"memory":[65],"(LSTM)":[66],"combined":[67,111],"models":[68],"missing-insensitive":[70],"Specifically,":[73],"autoencoder":[74,77,80,85],"(AE),":[75],"denoising":[76,83],"(DAE),":[78],"convolutional":[79,84],"(CAE),":[81],"(DCAE)":[86],"are":[87,97],"extracting":[90],"features,":[91],"which":[93],"the":[94,100,108,132],"encoded":[95],"outputs":[96],"fed":[98],"into":[99],"input":[101],"LSTM.":[103,134],"Our":[104],"experiments":[105],"show":[106],"proposed":[109],"DCAE/LSTM":[110],"model":[112],"significantly":[113],"improves":[114],"accuracy":[116],"no":[117],"matter":[118],"what":[119],"rate":[121],"or":[122],"type":[123],"(random":[124],"missing,":[125],"consecutive":[126],"block":[127],"missing)":[128],"occurs":[129],"compared":[130],"to":[131],"baseline":[133]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}