{"id":"https://openalex.org/W4293150140","doi":"https://doi.org/10.1155/2022/2993184","title":"Deep Learning\u2010Assisted Short\u2010Term Power Load Forecasting Using Deep Convolutional LSTM and Stacked GRU","display_name":"Deep Learning\u2010Assisted Short\u2010Term Power Load Forecasting Using Deep Convolutional LSTM and Stacked GRU","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4293150140","doi":"https://doi.org/10.1155/2022/2993184"},"language":"en","primary_location":{"id":"doi:10.1155/2022/2993184","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/2993184","pdf_url":"https://downloads.hindawi.com/journals/complexity/2022/2993184.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2022/2993184.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034260529","display_name":"Fath U Min Ullah","orcid":"https://orcid.org/0000-0002-1243-9358"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Fath U Min Ullah","raw_affiliation_strings":["Sejong University, Seoul 143-747"],"raw_orcid":"https://orcid.org/0000-0002-1243-9358","affiliations":[{"raw_affiliation_string":"Sejong University, Seoul 143-747","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075042717","display_name":"Amin Ullah","orcid":"https://orcid.org/0000-0001-7538-2689"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amin Ullah","raw_affiliation_strings":["Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University, Corvallis, OR, USA","Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University, Corvallis, OR"],"raw_orcid":"https://orcid.org/0000-0001-7538-2689","affiliations":[{"raw_affiliation_string":"Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University, Corvallis, OR, USA","institution_ids":["https://openalex.org/I131249849"]},{"raw_affiliation_string":"Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054308631","display_name":"Noman Khan","orcid":"https://orcid.org/0000-0001-7531-3827"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Noman Khan","raw_affiliation_strings":["Sejong University, Seoul 143-747, Republic of Korea","Sejong University, Seoul 143-747"],"raw_orcid":"https://orcid.org/0000-0001-7531-3827","affiliations":[{"raw_affiliation_string":"Sejong University, Seoul 143-747, Republic of Korea","institution_ids":["https://openalex.org/I28777354"]},{"raw_affiliation_string":"Sejong University, Seoul 143-747","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690117","display_name":"Mi Young Lee","orcid":"https://orcid.org/0000-0002-8139-7091"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mi Young Lee","raw_affiliation_strings":["Sejong University, Seoul 143-747, Republic of Korea","Sejong University, Seoul 143-747"],"raw_orcid":"https://orcid.org/0000-0002-8139-7091","affiliations":[{"raw_affiliation_string":"Sejong University, Seoul 143-747, Republic of Korea","institution_ids":["https://openalex.org/I28777354"]},{"raw_affiliation_string":"Sejong University, Seoul 143-747","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073263477","display_name":"Seungmin Rho","orcid":"https://orcid.org/0000-0003-1936-6785"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungmin Rho","raw_affiliation_strings":["Department of Industrial Security, Chung-Ang University, Seoul 06974, Republic of Korea","Department of Industrial Security, Chung-Ang University, Seoul 06974"],"raw_orcid":"https://orcid.org/0000-0003-1936-6785","affiliations":[{"raw_affiliation_string":"Department of Industrial Security, Chung-Ang University, Seoul 06974, Republic of Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Department of Industrial Security, Chung-Ang University, Seoul 06974","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072407810","display_name":"Sung Wook Baik","orcid":"https://orcid.org/0000-0002-6678-7788"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sung Wook Baik","raw_affiliation_strings":["Sejong University, Seoul 143-747, Republic of Korea","Sejong University, Seoul 143-747"],"raw_orcid":"https://orcid.org/0000-0002-6678-7788","affiliations":[{"raw_affiliation_string":"Sejong University, Seoul 143-747, Republic of Korea","institution_ids":["https://openalex.org/I28777354"]},{"raw_affiliation_string":"Sejong University, Seoul 143-747","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5072407810"],"corresponding_institution_ids":["https://openalex.org/I28777354"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":3.0465,"has_fulltext":true,"cited_by_count":36,"citation_normalized_percentile":{"value":0.91931387,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"2022","issue":"1","first_page":null,"last_page":null},"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":0.9887999892234802,"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/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.9871000051498413,"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/deep-learning","display_name":"Deep learning","score":0.7913424372673035},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.7371302843093872},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6968247294425964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6888434290885925},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6108564138412476},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.41253572702407837},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39385324716567993},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38869553804397583}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7913424372673035},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.7371302843093872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6968247294425964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6888434290885925},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6108564138412476},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.41253572702407837},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39385324716567993},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38869553804397583},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2022/2993184","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/2993184","pdf_url":"https://downloads.hindawi.com/journals/complexity/2022/2993184.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:2993184","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/complexity/2022/2993184.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:1b968f658419406c9d9f0107425f8fbc","is_oa":true,"landing_page_url":"https://doaj.org/article/1b968f658419406c9d9f0107425f8fbc","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":"Complexity, Vol 2022 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2022/2993184","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/2993184","pdf_url":"https://downloads.hindawi.com/journals/complexity/2022/2993184.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2438603286","display_name":null,"funder_award_id":"2019M3F2A1073179","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4293150140.pdf","grobid_xml":"https://content.openalex.org/works/W4293150140.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W1689711448","https://openalex.org/W1991277158","https://openalex.org/W2008750647","https://openalex.org/W2060765057","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2106857564","https://openalex.org/W2116435618","https://openalex.org/W2130942839","https://openalex.org/W2176490941","https://openalex.org/W2232980359","https://openalex.org/W2295959395","https://openalex.org/W2511775542","https://openalex.org/W2549906944","https://openalex.org/W2597866042","https://openalex.org/W2747580724","https://openalex.org/W2750021257","https://openalex.org/W2763500568","https://openalex.org/W2776741657","https://openalex.org/W2778221222","https://openalex.org/W2780699625","https://openalex.org/W2781966338","https://openalex.org/W2785428335","https://openalex.org/W2796265311","https://openalex.org/W2812669263","https://openalex.org/W2883326783","https://openalex.org/W2889386826","https://openalex.org/W2893898383","https://openalex.org/W2895889688","https://openalex.org/W2903969466","https://openalex.org/W2910849319","https://openalex.org/W2911794652","https://openalex.org/W2915736901","https://openalex.org/W2920901284","https://openalex.org/W2948490758","https://openalex.org/W2982807677","https://openalex.org/W2990125784","https://openalex.org/W2997861936","https://openalex.org/W3040251430","https://openalex.org/W3095115669","https://openalex.org/W3114369269","https://openalex.org/W3118620764","https://openalex.org/W3137976710","https://openalex.org/W3154413738","https://openalex.org/W3181894699","https://openalex.org/W3203160579","https://openalex.org/W4200590163","https://openalex.org/W4206158782","https://openalex.org/W6679436768"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2980611886","https://openalex.org/W42295635","https://openalex.org/W1973996291","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Over":[0],"the":[1,30,34,41,58,84,102,106,113,117,135,139,143,165,172,193,196],"decades,":[2],"a":[3,125,154],"rapid":[4],"upsurge":[5],"in":[6,57],"electricity":[7,86],"demand":[8],"has":[9],"been":[10],"observed":[11],"due":[12],"to":[13,25,82],"overpopulation":[14],"and":[15,28,49,60,76,141,183,189],"technological":[16],"growth.":[17],"The":[18,63,146],"optimum":[19],"production":[20],"of":[21,65,119,192],"energy":[22,31,43,70],"is":[23,122,150],"mandatory":[24],"preserve":[26],"it":[27],"improve":[29],"infrastructure":[32],"using":[33,178,195],"power":[35,198],"load":[36,199],"forecasting":[37],"(PLF)":[38],"method.":[39],"However,":[40],"complex":[42,69],"systems\u2019":[44],"transition":[45],"towards":[46],"more":[47],"robust":[48],"intelligent":[50,78,94],"system":[51],"will":[52],"ensure":[53],"its":[54],"momentous":[55],"role":[56],"industrial":[59],"economical":[61],"world.":[62],"extraction":[64],"deep":[66,79,95,155],"knowledge":[67],"from":[68,105,138],"data":[71,103,121],"patterns":[72],"requires":[73],"an":[74,93],"efficient":[75],"computationally":[77],"learning\u2010based":[80,96],"method":[81,98,174],"examine":[83],"future":[85],"demand.":[87],"Stand":[88],"by":[89],"this,":[90],"we":[91],"propose":[92],"PLF":[97],"where":[99],"at":[100],"first":[101],"collected":[104],"house":[107],"through":[108],"meters":[109],"are":[110],"fed":[111],"into":[112,124,153],"pre\u2010assessment":[114],"step.":[115],"Next,":[116],"sequence":[118,140],"refined":[120],"passed":[123],"modified":[126],"convolutional":[127],"long":[128],"short\u2010term":[129],"memory":[130],"(ConvLSTM)":[131],"network":[132,160],"that":[133,171],"captures":[134],"spatiotemporal":[136],"correlations":[137],"generates":[142],"feature":[144,148],"maps.":[145],"generated":[147],"map":[149],"forward":[151],"propagated":[152],"gated":[156],"recurrent":[157],"unit":[158],"(GRU)":[159],"for":[161],"learning,":[162],"which":[163],"provides":[164],"final":[166],"PLF.":[167],"We":[168],"experimentally":[169],"proved":[170],"proposed":[173],"revealed":[175],"promising":[176],"results":[177],"mean":[179,185],"square":[180,186],"error":[181,187],"(MSE)":[182],"root":[184],"(RMSE)":[188],"outperformed":[190],"state":[191],"art":[194],"competitive":[197],"dataset.(Github":[200],"Code).":[201],"(Github":[202],"code:":[203],"https://github.com/FathUMinUllah3797/ConvLSTM-Deep_GRU":[204],").":[205]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}