{"id":"https://openalex.org/W4404787904","doi":"https://doi.org/10.1109/access.2024.3507154","title":"Overcoming Data Scarcity in Wind Power Forecasting: A Deep Learning Approach With Bidirectional Generative Adversarial Network and Neighborhood Search PSO Algorithm","display_name":"Overcoming Data Scarcity in Wind Power Forecasting: A Deep Learning Approach With Bidirectional Generative Adversarial Network and Neighborhood Search PSO Algorithm","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4404787904","doi":"https://doi.org/10.1109/access.2024.3507154"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3507154","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3507154","pdf_url":null,"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://doi.org/10.1109/access.2024.3507154","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101863792","display_name":"Shiyu Liu","orcid":"https://orcid.org/0000-0003-0689-5100"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shiyu Liu","raw_affiliation_strings":["School of Digital Economics and Management, Wuxi University, Wuxi, China"],"affiliations":[{"raw_affiliation_string":"School of Digital Economics and Management, Wuxi University, Wuxi, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405442","display_name":"Fei Chen","orcid":"https://orcid.org/0000-0003-4397-0931"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Chen","raw_affiliation_strings":["CHN ENERGY I&C Interconnection Technology Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"CHN ENERGY I&C Interconnection Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039593319","display_name":"Zhendong Liu","orcid":"https://orcid.org/0009-0007-4058-3000"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhendong Liu","raw_affiliation_strings":["China Xinghua Electrical Sciences Research Institute Company Ltd., Kowloon, Hong Kong"],"affiliations":[{"raw_affiliation_string":"China Xinghua Electrical Sciences Research Institute Company Ltd., Kowloon, Hong Kong","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036969627","display_name":"Hongyan Qiao","orcid":"https://orcid.org/0000-0002-4833-4662"},"institutions":[{"id":"https://openalex.org/I4210144436","display_name":"Shanghai Huayi Group (China)","ror":"https://ror.org/044f58834","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210144436"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Qiao","raw_affiliation_strings":["Wuxi Yunyin Technology Group Company Ltd., Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Wuxi Yunyin Technology Group Company Ltd., Jiangsu, China","institution_ids":["https://openalex.org/I4210144436"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101863792"],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.4614,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.650711,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"12","issue":null,"first_page":"183410","last_page":"183428"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9976999759674072,"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":0.9976999759674072,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9455000162124634,"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/adversarial-system","display_name":"Adversarial system","score":0.8249310851097107},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.7527756690979004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6977334022521973},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5692489743232727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5138976573944092},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.46337878704071045},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37550830841064453},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3472835123538971},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.10549327731132507},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08967608213424683}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8249310851097107},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.7527756690979004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6977334022521973},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5692489743232727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5138976573944092},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.46337878704071045},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37550830841064453},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3472835123538971},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.10549327731132507},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08967608213424683},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3507154","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3507154","pdf_url":null,"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:325db0eeaa904f8cba4824fd6f77c721","is_oa":true,"landing_page_url":"https://doaj.org/article/325db0eeaa904f8cba4824fd6f77c721","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 183410-183428 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3507154","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3507154","pdf_url":null,"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":[{"display_name":"Affordable and clean energy","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W863118248","https://openalex.org/W1705374184","https://openalex.org/W2142809749","https://openalex.org/W2329476579","https://openalex.org/W2600292797","https://openalex.org/W2624832571","https://openalex.org/W2739824434","https://openalex.org/W2742197121","https://openalex.org/W2765759757","https://openalex.org/W2792011677","https://openalex.org/W2890139949","https://openalex.org/W2896194880","https://openalex.org/W2948535221","https://openalex.org/W2979550546","https://openalex.org/W3000694574","https://openalex.org/W3005209402","https://openalex.org/W3010227527","https://openalex.org/W3034941184","https://openalex.org/W3047348012","https://openalex.org/W3087054157","https://openalex.org/W3095043043","https://openalex.org/W3096831136","https://openalex.org/W3111349778","https://openalex.org/W3120107426","https://openalex.org/W3121826667","https://openalex.org/W3196068745","https://openalex.org/W3200304500","https://openalex.org/W3201319866","https://openalex.org/W3203929737","https://openalex.org/W3210818346","https://openalex.org/W4200052800","https://openalex.org/W4200202183","https://openalex.org/W4213137001","https://openalex.org/W4284671163","https://openalex.org/W4284971318","https://openalex.org/W4293762926","https://openalex.org/W4309049997","https://openalex.org/W4311303625","https://openalex.org/W4312579371","https://openalex.org/W4313215811","https://openalex.org/W4383371288","https://openalex.org/W4386377736","https://openalex.org/W4386783396","https://openalex.org/W4386874004","https://openalex.org/W6747491877"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"The":[0],"precision":[1],"and":[2,95,114,132,210,223],"stability":[3],"of":[4,15,22,44,68,75,121,208,221,227,235],"wind":[5,16,38,49,236],"power":[6,50,239],"prediction":[7,31,63,138,182,205],"(WPP)":[8],"are":[9],"critical":[10,158],"for":[11,27,36,149,242],"the":[12,19,42,66,73,103,119,129,133,137,170,176,181,192,219,225,228,233],"grid-connected":[13],"operation":[14],"farms.":[17],"However,":[18],"insufficient":[20],"availability":[21],"historical":[23,246],"data":[24,104],"poses":[25],"challenges":[26],"traditional":[28,122],"deep":[29],"learning":[30],"models":[32],"to":[33,110,143,157,162,167,179,199,218,231],"accurately":[34],"forecast":[35],"new-built":[37],"farms":[39,237],"(NWF)":[40],"under":[41],"background":[43],"a":[45,80,145,200],"substantial":[46],"increase":[47],"in":[48,60,78,187,238],"installed":[51],"capacity":[52],"worldwide.":[53],"Hence,":[54],"there":[55],"is":[56,85,108,141,173],"practical":[57],"scientific":[58],"significance":[59],"exploring":[61],"high-precision":[62],"methods":[64,198],"within":[65],"domain":[67],"NWF":[69],"WPP.":[70],"To":[71],"address":[72],"challenge":[74],"few":[76],"sample":[77],"WPP,":[79],"novel":[81,216],"data-enhanced":[82],"WPP":[83,222],"method":[84],"proposed,":[86],"which":[87],"integrates":[88],"BiGAN":[89,107],"(BiGAN)":[90],"module,":[91,106],"self-attention":[92],"mechanism":[93],"(SAM)":[94],"neighborhood":[96],"search":[97],"particle":[98],"swarm":[99],"optimization":[100],"(NSPSO).":[101],"Within":[102],"enhancement":[105],"proposed":[109,193,229],"mitigate":[111],"convergence":[112],"difficulties":[113],"gradient":[115],"instability":[116],"encountered":[117],"during":[118],"training":[120],"GANs,":[123],"thereby":[124],"fostering":[125],"closer":[126],"alignment":[127],"between":[128],"generated":[130],"distribution":[131],"real":[134],"distribution.":[135],"During":[136],"stage,":[139],"SAM":[140],"designed":[142],"obtain":[144],"new":[146],"input":[147,159],"matrix":[148],"weight":[150],"allocation":[151],"before":[152],"BiGRU,":[153],"enhancing":[154],"its":[155],"sensitivity":[156],"information.":[160],"Furthermore,":[161],"prevent":[163],"SAM-BiGRU":[164],"from":[165],"succumbing":[166],"local":[168],"optima,":[169],"Dense":[171],"layer":[172],"optimized":[174],"by":[175],"NSPSO":[177],"algorithm":[178],"improve":[180,232],"accuracy.":[183],"Extensive":[184],"experimental":[185],"results":[186],"two":[188],"scenarios":[189],"demonstrate":[190],"that":[191],"approach":[194],"surpasses":[195],"other":[196],"advanced":[197],"certain":[201],"extent,":[202],"achieving":[203],"one-step-ahead":[204],"accuracy":[206,234],"rates":[207],"0.9775":[209],"0.9810,":[211],"respectively.":[212],"This":[213],"study":[214],"provides":[215],"ideas":[217],"field":[220],"demonstrates":[224],"potential":[226],"model":[230],"prediction,":[240],"especially":[241],"those":[243],"with":[244],"limited":[245],"data.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}