{"id":"https://openalex.org/W4367281095","doi":"https://doi.org/10.1109/jsyst.2023.3265982","title":"Day-Ahead Spatiotemporal Wind Speed Forecasting Based on a Hybrid Model of Quantum and Residual Long Short-Term Memory Optimized by Particle Swarm Algorithm","display_name":"Day-Ahead Spatiotemporal Wind Speed Forecasting Based on a Hybrid Model of Quantum and Residual Long Short-Term Memory Optimized by Particle Swarm Algorithm","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4367281095","doi":"https://doi.org/10.1109/jsyst.2023.3265982"},"language":"en","primary_location":{"id":"doi:10.1109/jsyst.2023.3265982","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsyst.2023.3265982","pdf_url":null,"source":{"id":"https://openalex.org/S95999327","display_name":"IEEE Systems Journal","issn_l":"1932-8184","issn":["1932-8184","1937-9234","2373-7816"],"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 Systems Journal","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/A5101453079","display_name":"Ying\u2010Yi Hong","orcid":"https://orcid.org/0000-0002-9540-3931"},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Ying Yi Hong","raw_affiliation_strings":["Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I151221077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091741541","display_name":"Jay Bhie D. Santos","orcid":"https://orcid.org/0009-0002-3130-4106"},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jay Bhie D. Santos","raw_affiliation_strings":["Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I151221077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101453079"],"corresponding_institution_ids":["https://openalex.org/I151221077"],"apc_list":null,"apc_paid":null,"fwci":1.7352,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84350377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":1.0,"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":1.0,"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/T14444","display_name":"Power Systems and Renewable Energy","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2102","display_name":"Energy Engineering and Power Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10424","display_name":"Electric Power System Optimization","score":0.9939000010490417,"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/wind-power","display_name":"Wind power","score":0.6557124257087708},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6524682641029358},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6160659193992615},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.572152316570282},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.5693204998970032},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5244320034980774},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.49101948738098145},{"id":"https://openalex.org/keywords/intermittency","display_name":"Intermittency","score":0.4379866421222687},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4317912459373474},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42119771242141724},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4202682375907898},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34465450048446655},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.189103364944458},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.08971080183982849}],"concepts":[{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.6557124257087708},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6524682641029358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6160659193992615},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.572152316570282},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.5693204998970032},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5244320034980774},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.49101948738098145},{"id":"https://openalex.org/C2780388094","wikidata":"https://www.wikidata.org/wiki/Q1666248","display_name":"Intermittency","level":3,"score":0.4379866421222687},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4317912459373474},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42119771242141724},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4202682375907898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34465450048446655},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.189103364944458},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.08971080183982849},{"id":"https://openalex.org/C196558001","wikidata":"https://www.wikidata.org/wiki/Q190132","display_name":"Turbulence","level":2,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jsyst.2023.3265982","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsyst.2023.3265982","pdf_url":null,"source":{"id":"https://openalex.org/S95999327","display_name":"IEEE Systems Journal","issn_l":"1932-8184","issn":["1932-8184","1937-9234","2373-7816"],"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 Systems Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2266215525","display_name":null,"funder_award_id":"NL1110107","funder_id":"https://openalex.org/F4320323145","funder_display_name":"Institute of Nuclear Energy Research"},{"id":"https://openalex.org/G2752945347","display_name":null,"funder_award_id":"111A010","funder_id":"https://openalex.org/F4320323145","funder_display_name":"Institute of Nuclear Energy Research"}],"funders":[{"id":"https://openalex.org/F4320323145","display_name":"Institute of Nuclear Energy Research","ror":"https://ror.org/052jx3443"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1568345435","https://openalex.org/W2048340369","https://openalex.org/W2049874822","https://openalex.org/W2105614108","https://openalex.org/W2187207171","https://openalex.org/W2194775991","https://openalex.org/W2766652992","https://openalex.org/W2773390159","https://openalex.org/W2781738013","https://openalex.org/W2796072231","https://openalex.org/W2806029326","https://openalex.org/W2897551149","https://openalex.org/W2914466649","https://openalex.org/W2946405318","https://openalex.org/W2963917928","https://openalex.org/W2973461110","https://openalex.org/W2989257188","https://openalex.org/W3083636819","https://openalex.org/W3100931082","https://openalex.org/W3112613839","https://openalex.org/W3117249234","https://openalex.org/W3158610431","https://openalex.org/W3208616775","https://openalex.org/W3212952282","https://openalex.org/W3217410715","https://openalex.org/W4205129187","https://openalex.org/W4210683819","https://openalex.org/W4289606390","https://openalex.org/W4297802473","https://openalex.org/W4303083877","https://openalex.org/W6634007516","https://openalex.org/W6687250854","https://openalex.org/W6755964158","https://openalex.org/W6782813041"],"related_works":["https://openalex.org/W2564644595","https://openalex.org/W1589804082","https://openalex.org/W1566002589","https://openalex.org/W2042838258","https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2075007075","https://openalex.org/W2783018065","https://openalex.org/W1525560163","https://openalex.org/W2146343568"],"abstract_inverted_index":{"Fluctuations":[0],"in":[1,5],"wind":[2,7,14,78],"speed":[3,33,79],"result":[4],"intermittent":[6],"power":[8,12,15,42],"generation.":[9],"In":[10],"a":[11,57,112],"grid,":[13],"intermittency":[16],"has":[17],"serious":[18],"repercussions,":[19],"including":[20],"poor":[21],"system":[22],"reliability,":[23],"increased":[24,29],"reserve":[25],"capacity":[26],"requirement,":[27],"and":[28,49,63,89,92,135,141],"operating":[30],"costs.":[31],"Wind":[32],"must":[34],"be":[35],"accurately":[36],"predicted":[37],"to":[38,44,118,125],"enable":[39],"the":[40,51,93,97,106,109,119,126,129],"day-ahead":[41,76],"market":[43,52],"schedule":[45],"dispatchable":[46],"generation":[47],"resources":[48],"determine":[50],"prices.":[53],"This":[54],"article":[55],"proposes":[56],"novel":[58],"hybrid":[59],"model":[60,131],"of":[61,96,108],"quantum":[62,113],"residual":[64,98],"long":[65],"short-term":[66],"memory":[67],"(LSTM)":[68],"optimized":[69,120],"by":[70,102],"particle":[71],"swarm":[72],"optimization":[73],"(PSO)":[74],"for":[75],"spatiotemporal":[77],"forecasting.":[80],"The":[81],"hyperparameters":[82],"(time":[83],"series,":[84],"time":[85],"lag,":[86],"dropout":[87],"rate,":[88],"learning":[90,139,143],"rate)":[91],"structure":[94],"parameter":[95],"LSTM":[99],"are":[100],"tuned":[101],"PSO.":[103],"To":[104],"improve":[105],"accuracy":[107],"proposed":[110,130],"model,":[111],"embedding":[114],"layer":[115],"is":[116,132],"added":[117],"residual-LSTM":[121],"neural":[122],"network.":[123],"According":[124],"test":[127],"results,":[128],"highly":[133],"accurate":[134],"outperforms":[136],"numerous":[137],"machine":[138],"methods":[140],"deep":[142],"algorithms.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-08T08:50:53.379069","created_date":"2025-10-10T00:00:00"}