{"id":"https://openalex.org/W4415744135","doi":"https://doi.org/10.1109/qrs-c65679.2025.00022","title":"Short-Term Wind Power Forecasting Method Based on Improved iTransformer","display_name":"Short-Term Wind Power Forecasting Method Based on Improved iTransformer","publication_year":2025,"publication_date":"2025-07-16","ids":{"openalex":"https://openalex.org/W4415744135","doi":"https://doi.org/10.1109/qrs-c65679.2025.00022"},"language":null,"primary_location":{"id":"doi:10.1109/qrs-c65679.2025.00022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qrs-c65679.2025.00022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 25th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","raw_type":"proceedings-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/A5014888283","display_name":"Zhiyong An","orcid":"https://orcid.org/0000-0003-1252-3872"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhilong An","raw_affiliation_strings":["Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China"],"affiliations":[{"raw_affiliation_string":"Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370846","display_name":"Yuezhong Wu","orcid":"https://orcid.org/0000-0002-3618-6068"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuezhong Wu","raw_affiliation_strings":["Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China"],"affiliations":[{"raw_affiliation_string":"Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054100818","display_name":"Lingjiao Chen","orcid":"https://orcid.org/0009-0007-2824-6220"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjiao Chen","raw_affiliation_strings":["Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China"],"affiliations":[{"raw_affiliation_string":"Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107846607","display_name":"Dawei He","orcid":null},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei He","raw_affiliation_strings":["Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China"],"affiliations":[{"raw_affiliation_string":"Hunan University of Technology,School of Traffic and Electrical Engineering,Zhuzhou,China","institution_ids":["https://openalex.org/I49934816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014888283"],"corresponding_institution_ids":["https://openalex.org/I49934816"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30765576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"91","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.988099992275238,"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":0.988099992275238,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.0010999999940395355,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10740","display_name":"Wind Turbine Control Systems","score":0.0010999999940395355,"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":0.8205000162124634},{"id":"https://openalex.org/keywords/wind-power-forecasting","display_name":"Wind power forecasting","score":0.781000018119812},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.44699999690055847},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.42399999499320984},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4185999929904938},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.40529999136924744},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.4050000011920929}],"concepts":[{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.8205000162124634},{"id":"https://openalex.org/C2781084341","wikidata":"https://www.wikidata.org/wiki/Q2583670","display_name":"Wind power forecasting","level":4,"score":0.781000018119812},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.44699999690055847},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44510000944137573},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4185999929904938},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.4050000011920929},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4004000127315521},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3813999891281128},{"id":"https://openalex.org/C174303752","wikidata":"https://www.wikidata.org/wiki/Q3624438","display_name":"Forecast error","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.28459998965263367},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2759000062942505},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.26820001006126404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/qrs-c65679.2025.00022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qrs-c65679.2025.00022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 25th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W317957491","https://openalex.org/W1968112823","https://openalex.org/W1973778471","https://openalex.org/W1981047607","https://openalex.org/W2230957558","https://openalex.org/W2565639579","https://openalex.org/W2963131120","https://openalex.org/W3000440908","https://openalex.org/W3090661556","https://openalex.org/W3135463282","https://openalex.org/W4292072103","https://openalex.org/W4293038943","https://openalex.org/W4308128268","https://openalex.org/W4323838614","https://openalex.org/W4383955976","https://openalex.org/W4385245566","https://openalex.org/W4385819865","https://openalex.org/W4386921320","https://openalex.org/W4393863660","https://openalex.org/W4400141094"],"related_works":[],"abstract_inverted_index":{"The":[0,146],"volatility":[1],"of":[2,16,26,35,42,136,151],"wind":[3,9,27,36,43,51,65,77,115,123,157],"energy":[4,52],"poses":[5],"challenges":[6],"to":[7,108],"large-scale":[8],"power":[10,17,21,37,44,66,78,116,124,158,166],"grid":[11,167],"integration,":[12],"exacerbating":[13],"the":[14,24,33,40,82,114,128,149,152],"risk":[15],"system":[18],"imbalance.":[19],"Wind":[20],"forecasting":[22,45,57,67,159],"enables":[23],"estimation":[25],"farm":[28],"output":[29],"fluctuations,":[30],"effectively":[31],"reducing":[32],"uncertainty":[34],"generation.":[38],"Improving":[39],"accuracy":[41],"is":[46,106],"crucial":[47],"for":[48,165],"enhanc":[49],"ing":[50],"utilization":[53],"efficiency.":[54],"To":[55,72],"enhance":[56],"precision,":[58],"this":[59],"paper":[60],"proposes":[61],"an":[62],"improved":[63],"short-term":[64,156],"method":[68,130,154],"based":[69],"on":[70,120],"iTransformer.":[71],"address":[73],"noise":[74,93],"interference":[75],"in":[76,94,134,155],"data,":[79],"we":[80],"introduce":[81],"FTDCycle":[83],"(Time-Frequency":[84],"Domain":[85],"Closed-Loop":[86],"Denoising)":[87],"mechanism,":[88],"which":[89],"jointly":[90],"suppresses":[91],"non-stationary":[92],"both":[95],"time":[96],"and":[97,141,160],"frequency":[98],"domains.":[99],"Subsequently,":[100],"RLKConv":[101],"(Reparameterized":[102],"Large":[103],"Kernel":[104],"Convolution)":[105],"employed":[107],"efficiently":[109],"extract":[110],"multi-scale":[111],"features":[112],"from":[113],"data.":[117],"Experimental":[118],"results":[119],"two":[121],"cross-regional":[122],"datasets":[125],"demonstrate":[126],"that":[127],"proposed":[129,153],"outperforms":[131],"existing":[132],"approaches":[133],"terms":[135],"Mean":[137,142],"Squared":[138],"Error":[139,144],"(MSE)":[140],"Absolute":[143],"(MAE).":[145],"findings":[147],"validate":[148],"effectiveness":[150],"provide":[161],"accurate":[162],"data":[163],"support":[164],"scheduling.":[168]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-31T00:00:00"}