{"id":"https://openalex.org/W3162682624","doi":"https://doi.org/10.1109/access.2021.3080140","title":"Ultra-Short-Term Prediction of Wind Power Based on Sample Similarity Analysis","display_name":"Ultra-Short-Term Prediction of Wind Power Based on Sample Similarity Analysis","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3162682624","doi":"https://doi.org/10.1109/access.2021.3080140","mag":"3162682624"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3080140","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3080140","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09430545.pdf","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://ieeexplore.ieee.org/ielx7/6287639/9312710/09430545.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048313465","display_name":"Changxin Miao","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changxin Miao","raw_affiliation_strings":["School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101577653","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-7390-4057"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7390-4057","affiliations":[{"raw_affiliation_string":"School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100711871","display_name":"Xia Wang","orcid":"https://orcid.org/0000-0001-7701-7722"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Wang","raw_affiliation_strings":["School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7701-7722","affiliations":[{"raw_affiliation_string":"School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100338815","display_name":"Heng Li","orcid":"https://orcid.org/0000-0003-1638-1752"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Li","raw_affiliation_strings":["School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1638-1752","affiliations":[{"raw_affiliation_string":"School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.9153,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.73684258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"72730","last_page":"72742"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9991999864578247,"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":0.9991999864578247,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13650","display_name":"Computational Physics and Python Applications","score":0.97079998254776,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6383710503578186},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.5970848798751831},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5952996015548706},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5744541883468628},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5449040532112122},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5439134240150452},{"id":"https://openalex.org/keywords/wind-power-forecasting","display_name":"Wind power forecasting","score":0.5259419083595276},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5066347718238831},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.5018100738525391},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.48664650321006775},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.473666250705719},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4661482572555542},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4647276699542999},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.43211090564727783},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42777252197265625},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3995819091796875},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3906354308128357},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.28035712242126465},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1450350284576416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6383710503578186},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.5970848798751831},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5952996015548706},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5744541883468628},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5449040532112122},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5439134240150452},{"id":"https://openalex.org/C2781084341","wikidata":"https://www.wikidata.org/wiki/Q2583670","display_name":"Wind power forecasting","level":4,"score":0.5259419083595276},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5066347718238831},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.5018100738525391},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.48664650321006775},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.473666250705719},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4661482572555542},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4647276699542999},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.43211090564727783},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42777252197265625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3995819091796875},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3906354308128357},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.28035712242126465},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1450350284576416},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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.2021.3080140","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3080140","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09430545.pdf","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:e16501a197af4e0da0465ffb868cbb47","is_oa":true,"landing_page_url":"https://doaj.org/article/e16501a197af4e0da0465ffb868cbb47","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":"IEEE Access, Vol 9, Pp 72730-72742 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3080140","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3080140","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09430545.pdf","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","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3162682624.pdf","grobid_xml":"https://content.openalex.org/works/W3162682624.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W373046421","https://openalex.org/W1185746543","https://openalex.org/W1650699486","https://openalex.org/W1985727987","https://openalex.org/W1994064251","https://openalex.org/W2034991783","https://openalex.org/W2036681246","https://openalex.org/W2038500579","https://openalex.org/W2051699975","https://openalex.org/W2065967299","https://openalex.org/W2070960910","https://openalex.org/W2079697937","https://openalex.org/W2106595237","https://openalex.org/W2113536687","https://openalex.org/W2153263933","https://openalex.org/W2168853698","https://openalex.org/W2243297718","https://openalex.org/W2284381800","https://openalex.org/W2294198843","https://openalex.org/W2319709116","https://openalex.org/W2321536237","https://openalex.org/W2328528054","https://openalex.org/W2469077086","https://openalex.org/W2566003805","https://openalex.org/W2571048075","https://openalex.org/W2598525681","https://openalex.org/W2600292797","https://openalex.org/W2749526959","https://openalex.org/W2754498139","https://openalex.org/W2769156605","https://openalex.org/W2781582701","https://openalex.org/W2794103404","https://openalex.org/W2810658548","https://openalex.org/W2884415573","https://openalex.org/W2893815961","https://openalex.org/W2896920734","https://openalex.org/W2898515673","https://openalex.org/W2900809110","https://openalex.org/W2902252637","https://openalex.org/W2908011629","https://openalex.org/W2914856364","https://openalex.org/W2923573337","https://openalex.org/W2929920051","https://openalex.org/W2980418403"],"related_works":["https://openalex.org/W2626641865","https://openalex.org/W2034182965","https://openalex.org/W3154413779","https://openalex.org/W2246158493","https://openalex.org/W2060606400","https://openalex.org/W2946066052","https://openalex.org/W2102851390","https://openalex.org/W2142241280","https://openalex.org/W4200305155","https://openalex.org/W1963538988"],"abstract_inverted_index":{"Increasing":[0],"the":[1,12,21,56,84,95,124,129,136,156,171,178,216,221],"utilization":[2],"rate":[3],"of":[4,8,14,23,53,58,73,86,174,183,220],"wind":[5,24,146,151],"energy":[6,15],"is":[7,18,31,36,98,120,139],"great":[9],"significance":[10],"to":[11,127,185],"improvement":[13],"structure,":[16],"which":[17,192],"inseparable":[19],"from":[20,83],"support":[22],"power":[25,147,152],"forecasting":[26],"(WPF)":[27],"technology.":[28],"However,":[29],"it":[30],"well":[32],"known":[33],"that":[34],"there":[35],"no":[37],"certain":[38],"WPF":[39,137],"model":[40,201],"suitable":[41],"for":[42,111],"all":[43],"conditions,":[44],"such":[45],"as":[46],"different":[47,104],"regions":[48],"or":[49],"seasons.":[50],"Therefore,":[51],"instead":[52],"focusing":[54],"on":[55,123,212],"combination":[57],"machine":[59],"learning":[60,173],"models":[61,108],"in":[62,92,115],"a":[63,69],"specific":[64,181],"scenario,":[65],"this":[66,134],"article":[67],"proposes":[68],"two-stage":[70],"modeling":[71],"strategy":[72],"\u201cfirst":[74],"classify":[75],"and":[76,106,150,158,164,188,202,218],"separately":[77],"model,":[78],"then":[79],"perform":[80],"pattern":[81,118],"recognition\u201d":[82],"perspective":[85],"sample":[87,126,175],"similarity":[88],"analysis.":[89],"That":[90],"is,":[91],"offline":[93],"mode,":[94,117],"historical":[96],"database":[97],"divided":[99],"into":[100,141],"multiple":[101],"categories":[102],"with":[103],"characteristics,":[105],"prediction":[107,125,131,166,207],"are":[109,168,190,193],"established":[110],"each":[112],"category":[113],"respectively;":[114],"online":[116],"recognition":[119],"carried":[121],"out":[122],"select":[128],"corresponding":[130],"model.":[132,224],"In":[133],"way,":[135],"problem":[138],"decomposed":[140],"two":[142],"strongly":[143],"related":[144],"tasks:":[145],"mode":[148,161],"classification":[149,162,200],"numerical":[153,165],"prediction.":[154],"Furthermore,":[155],"coupling":[157],"connection":[159],"between":[160],"task":[163,167],"strengthened":[169],"through":[170],"transfer":[172],"features.":[176],"Around":[177],"above":[179],"ideas,":[180],"methods":[182],"how":[184],"classify,":[186],"identify,":[187],"predict":[189],"proposed,":[191],"two-level":[194],"clustering,":[195],"Convolutional":[196],"Neural":[197],"Network":[198],"(CNN)":[199],"Long":[203],"Short-term":[204],"Memory":[205],"(LSTM)":[206],"models.":[208],"Simulation":[209],"results":[210],"based":[211],"real-world":[213],"datasets":[214],"prove":[215],"effectiveness":[217],"superiority":[219],"proposed":[222],"hybrid":[223]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
