{"id":"https://openalex.org/W4413967104","doi":"https://doi.org/10.1109/tsg.2025.3605653","title":"A Multi-Task End-to-End Multivariate Long-Sequence Time Series Prediction Model for Load Forecasting","display_name":"A Multi-Task End-to-End Multivariate Long-Sequence Time Series Prediction Model for Load Forecasting","publication_year":2025,"publication_date":"2025-09-03","ids":{"openalex":"https://openalex.org/W4413967104","doi":"https://doi.org/10.1109/tsg.2025.3605653"},"language":"en","primary_location":{"id":"doi:10.1109/tsg.2025.3605653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2025.3605653","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"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 Smart Grid","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/A5100730159","display_name":"Ziyuan Zhang","orcid":"https://orcid.org/0000-0002-4547-5283"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyuan Zhang","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010845083","display_name":"Yuanzheng Li","orcid":"https://orcid.org/0000-0001-8052-1233"},"institutions":[{"id":"https://openalex.org/I179060312","display_name":"Northeast Electric Power University","ror":"https://ror.org/00zqaxa34","country_code":"CN","type":"education","lineage":["https://openalex.org/I179060312"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanzheng Li","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","School of Electrical Engineering, Northeast Electric Power University, Jilin City, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]},{"raw_affiliation_string":"School of Electrical Engineering, Northeast Electric Power University, Jilin City, China","institution_ids":["https://openalex.org/I179060312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421591","display_name":"Yang Li","orcid":"https://orcid.org/0000-0002-6515-4567"},"institutions":[{"id":"https://openalex.org/I179060312","display_name":"Northeast Electric Power University","ror":"https://ror.org/00zqaxa34","country_code":"CN","type":"education","lineage":["https://openalex.org/I179060312"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","School of Electrical Engineering, Northeast Electric Power University, Jilin City, China","School of Electrical Engineering, Northeast Electric Power University, Jilin, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]},{"raw_affiliation_string":"School of Electrical Engineering, Northeast Electric Power University, Jilin City, China","institution_ids":["https://openalex.org/I179060312"]},{"raw_affiliation_string":"School of Electrical Engineering, Northeast Electric Power University, Jilin, China","institution_ids":["https://openalex.org/I179060312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054200960","display_name":"Yun Liu","orcid":"https://orcid.org/0000-0002-1370-4467"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Liu","raw_affiliation_strings":["School of Electric Power Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electric Power Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066409796","display_name":"Xiangpeng Xie","orcid":"https://orcid.org/0000-0003-4822-3134"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangpeng Xie","raw_affiliation_strings":["Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081245089","display_name":"Zhigang Zeng","orcid":"https://orcid.org/0000-0003-4587-3588"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Zeng","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100730159"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":19.879,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.99171015,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"17","issue":"1","first_page":"715","last_page":"732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.961899995803833,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.961899995803833,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T14392","display_name":"Geoscience and Mining Technology","score":0.9445000290870667,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9329000115394592,"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/multivariate-statistics","display_name":"Multivariate statistics","score":0.7053717374801636},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.61990886926651},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6196385025978088},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5815878510475159},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5724228620529175},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.5649937987327576},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5181373357772827},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3392029404640198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3074530363082886},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2335960566997528},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.225408136844635}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7053717374801636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.61990886926651},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6196385025978088},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5815878510475159},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5724228620529175},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.5649937987327576},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5181373357772827},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3392029404640198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3074530363082886},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2335960566997528},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.225408136844635},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsg.2025.3605653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2025.3605653","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"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 Smart Grid","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G148096710","display_name":null,"funder_award_id":"52377081","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6340177522","display_name":null,"funder_award_id":"62422308","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":26,"referenced_works":["https://openalex.org/W2151767444","https://openalex.org/W2200377847","https://openalex.org/W2268377817","https://openalex.org/W2552991604","https://openalex.org/W2754252319","https://openalex.org/W3006962611","https://openalex.org/W3007211815","https://openalex.org/W3088383850","https://openalex.org/W3110538917","https://openalex.org/W3129054759","https://openalex.org/W3177318507","https://openalex.org/W4226020959","https://openalex.org/W4226322096","https://openalex.org/W4234060530","https://openalex.org/W4285297243","https://openalex.org/W4312684895","https://openalex.org/W4316661065","https://openalex.org/W4382203079","https://openalex.org/W4384787520","https://openalex.org/W4386453649","https://openalex.org/W4388406189","https://openalex.org/W4391543989","https://openalex.org/W4391694085","https://openalex.org/W4400311289","https://openalex.org/W4403123403","https://openalex.org/W4410631409"],"related_works":["https://openalex.org/W2151749779","https://openalex.org/W3179968364","https://openalex.org/W1999612375","https://openalex.org/W2938107654","https://openalex.org/W2406638334","https://openalex.org/W3196421258","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"With":[0],"the":[1,5,9,87,95,108,113,162,165,168,183,197,216,223,238],"increasing":[2],"complexity":[3],"of":[4,19,49,128,131,175,248],"power":[6],"system,":[7],"and":[8,16,24,58,136,150,190,207,211,234],"growing":[10],"global":[11],"demand":[12],"for":[13,40,67],"electricity,":[14],"accurate":[15],"effective":[17],"forecasting":[18,77],"electricity":[20,22,42,54,56,68,132,134],"load,":[21,43,55],"prices,":[23,57,135],"related":[25,59,137],"meteorological":[26,60,138],"features":[27,139],"becomes":[28],"increasingly":[29],"crucial.":[30],"However,":[31],"existing":[32],"methods":[33,78],"tend":[34],"to":[35,70,107,250],"use":[36],"only":[37],"one":[38],"element,":[39],"example,":[41],"as":[44],"their":[45],"prediction":[46,109],"target":[47],"instead":[48],"generating":[50,196],"multiple":[51,81,103],"indexes":[52],"(e.g.,":[53],"features)":[61],"predictions":[62],"jointly.":[63],"This":[64],"is":[65,126,212],"insufficient":[66],"producers":[69],"make":[71],"decisions.":[72],"While":[73],"some":[74],"time":[75,232,247],"series":[76,104],"can":[79],"predict":[80],"indicators":[82],"simultaneously,":[83],"they":[84],"often":[85],"overlook":[86],"correlations":[88,101],"among":[89,102],"these":[90],"features.":[91],"These":[92],"approaches":[93],"miss":[94],"potential":[96],"performance":[97],"improvement":[98],"that":[99,222],"modeling":[100],"could":[105],"bring":[106],"results.":[110,199],"To":[111],"address":[112],"aforementioned":[114],"concerns,":[115],"this":[116,201],"study":[117],"presents":[118],"a":[119,141,154,244],"model":[120,146,202,225],"named":[121],"PatchGRU.":[122],"Once":[123],"trained,":[124],"PatchGRU":[125],"capable":[127],"predicting":[129],"long-sequences":[130],"loads,":[133],"in":[140,173,229,241],"single":[142],"forward":[143],"propagation.":[144],"The":[145],"differentiates":[147],"between":[148],"time-variant":[149,163],"time-invariant":[151],"components":[152],"using":[153],"Temporal":[155],"Variance":[156],"Separator,":[157],"processing":[158],"them":[159],"separately.":[160],"For":[161],"part,":[164],"network":[166],"uses":[167],"proposed":[169,224],"multi-scale":[170],"patch":[171],"input":[172],"place":[174],"traditional":[176],"point":[177],"inputs,":[178],"then":[179],"feeds":[180],"it":[181],"through":[182],"Gate":[184],"Recurrent":[185],"Unit":[186],"(GRU),":[187],"mean":[188],"supervision,":[189],"Local-Global":[191],"Feature":[192],"Interaction":[193],"modules,":[194],"ultimately":[195],"forecast":[198],"Moreover,":[200],"relies":[203],"solely":[204],"on":[205],"GRU":[206],"Multilayer":[208],"Perceptrons":[209],"(MLPs)":[210],"much":[213],"simpler":[214],"than":[215],"Transformer":[217],"structure.":[218],"Experimental":[219],"results":[220,240],"show":[221],"outperforms":[226],"state-of-the-art":[227],"models":[228],"different":[230],"regions,":[231],"periods,":[233],"sampling":[235],"frequencies,":[236],"achieving":[237],"best":[239],"forecasts":[242],"with":[243],"maximum":[245],"lead":[246],"up":[249],"30":[251],"days.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-29T08:15:47.926485","created_date":"2025-10-10T00:00:00"}