{"id":"https://openalex.org/W2285130932","doi":"https://doi.org/10.1142/s0218001416500117","title":"Day-Ahead Prediction of Wind Speed with Deep Feature Learning","display_name":"Day-Ahead Prediction of Wind Speed with Deep Feature Learning","publication_year":2016,"publication_date":"2016-01-21","ids":{"openalex":"https://openalex.org/W2285130932","doi":"https://doi.org/10.1142/s0218001416500117","mag":"2285130932"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001416500117","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001416500117","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5008331719","display_name":"Jie Wan","orcid":"https://orcid.org/0000-0002-4789-6049"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wan","raw_affiliation_strings":["School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101763629","display_name":"Jinfu Liu","orcid":"https://orcid.org/0000-0002-4590-5343"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinfu Liu","raw_affiliation_strings":["School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054961219","display_name":"Guorui Ren","orcid":"https://orcid.org/0000-0002-3525-2203"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guorui Ren","raw_affiliation_strings":["School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101789519","display_name":"Yufeng Guo","orcid":"https://orcid.org/0000-0001-8517-6184"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufeng Guo","raw_affiliation_strings":["School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100519691","display_name":"Daren Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daren Yu","raw_affiliation_strings":["School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Energy Science and Engineering, Harbin Institute of Technology, 150001 Harbin, Heilongjiang, P. R. China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056686459","display_name":"Qinghua Hu","orcid":"https://orcid.org/0000-0001-7765-8095"},"institutions":[{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Hu","raw_affiliation_strings":["School of Computer Science and Technology, Tianjin University, 300072 Tianjin, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tianjin University, 300072 Tianjin, P. R. China","institution_ids":["https://openalex.org/I132369690"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7584,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.84725596,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"30","issue":"05","first_page":"1650011","last_page":"1650011"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9902999997138977,"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/T10680","display_name":"Wind Energy Research and Development","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.8273888230323792},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.7939849495887756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7620841264724731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7113521695137024},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.649042010307312},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6362387537956238},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5677289962768555},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5314007997512817},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5193547010421753},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4695136249065399},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4484425485134125},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4430463910102844},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4394713044166565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41871386766433716}],"concepts":[{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.8273888230323792},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.7939849495887756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7620841264724731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7113521695137024},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.649042010307312},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6362387537956238},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5677289962768555},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5314007997512817},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5193547010421753},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4695136249065399},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4484425485134125},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4430463910102844},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4394713044166565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41871386766433716},{"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001416500117","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001416500117","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9200000166893005,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W60927318","https://openalex.org/W121264339","https://openalex.org/W219442790","https://openalex.org/W1491997873","https://openalex.org/W1519238132","https://openalex.org/W1545465591","https://openalex.org/W1556986061","https://openalex.org/W1705374184","https://openalex.org/W1901616594","https://openalex.org/W1966499742","https://openalex.org/W1968378534","https://openalex.org/W1970978817","https://openalex.org/W1981151789","https://openalex.org/W1984572828","https://openalex.org/W1996216733","https://openalex.org/W1997369014","https://openalex.org/W2007530458","https://openalex.org/W2021510303","https://openalex.org/W2036218954","https://openalex.org/W2036773138","https://openalex.org/W2037845744","https://openalex.org/W2039238531","https://openalex.org/W2043070647","https://openalex.org/W2050038283","https://openalex.org/W2076406292","https://openalex.org/W2077256327","https://openalex.org/W2077299262","https://openalex.org/W2083351521","https://openalex.org/W2086590688","https://openalex.org/W2092642094","https://openalex.org/W2117130368","https://openalex.org/W2124537004","https://openalex.org/W2136922672","https://openalex.org/W2140833774","https://openalex.org/W2141398217","https://openalex.org/W2143703772","https://openalex.org/W2149600041","https://openalex.org/W2162157229","https://openalex.org/W2163006955","https://openalex.org/W2163940180","https://openalex.org/W2165991108","https://openalex.org/W2167088383","https://openalex.org/W2168231600","https://openalex.org/W2263189687","https://openalex.org/W2503334840","https://openalex.org/W2546191734","https://openalex.org/W2919115771","https://openalex.org/W4231109964","https://openalex.org/W4246301727"],"related_works":["https://openalex.org/W3121598771","https://openalex.org/W2518528680","https://openalex.org/W2320963147","https://openalex.org/W3010338767","https://openalex.org/W2774529511","https://openalex.org/W2765084224","https://openalex.org/W1257380361","https://openalex.org/W2133034788","https://openalex.org/W2899839677","https://openalex.org/W2041493768"],"abstract_inverted_index":{"Day-ahead":[0,110],"prediction":[1,111,127,198,202,228],"of":[2,11,26,73,95,136,149,185,209,235],"wind":[3,13,27,51,69,186,248],"speed":[4,52,70,187,249],"is":[5,47,222],"a":[6,62,105,137,215,243],"basic":[7],"and":[8,37,81,98,134,166,181],"key":[9],"problem":[10],"large-scale":[12],"power":[14],"penetration.":[15],"Many":[16],"current":[17],"techniques":[18],"fail":[19],"to":[20,42,68,131,225],"satisfy":[21],"practical":[22,245],"engineering":[23],"requirements":[24],"because":[25,72],"speed's":[28],"strong":[29,190],"nonlinear":[30,191],"features,":[31],"influenced":[32],"by":[33,230],"many":[34],"complex":[35,183],"factors,":[36],"the":[38,119,126,150,176,207,227,233,239],"general":[39],"model's":[40,211],"inability":[41],"automatically":[43],"learn":[44,180],"features.":[45],"It":[46],"well":[48],"recognized":[49],"that":[50,125],"varies":[53],"in":[54],"different":[55],"patterns.":[56],"In":[57,174,200],"this":[58,219],"paper,":[59],"we":[60],"propose":[61],"deep":[63,85],"feature":[64,79],"learning":[65],"(DFL)":[66],"approach":[67],"forecasting":[71],"its":[74,189,197],"advantages":[75],"at":[76],"both":[77,132],"multi-layer":[78],"extraction":[80],"unsupervised":[82],"learning.":[83],"A":[84],"belief":[86],"network":[87],"(DBN)":[88],"model":[89,139,178],"for":[90,247],"regression":[91,158],"with":[92,129,140,169],"an":[93],"architecture":[94],"144":[96,99],"input":[97],"output":[100],"nodes":[101],"was":[102,123],"constructed":[103],"using":[104],"restricted":[106],"Boltzmann":[107],"machine":[108],"(RBM).":[109],"experiments":[112],"were":[113,145],"then":[114],"carried":[115],"out.":[116],"By":[117],"comparing":[118],"experimental":[120],"results,":[121],"it":[122,221],"found":[124],"errors":[128,203],"respect":[130],"size":[133],"stability":[135],"DBN":[138,177,210,240],"only":[141],"three":[142,152,170],"hidden":[143,161,171,212,236],"layers":[144,172,213],"less":[146],"than":[147],"those":[148],"other":[151],"typical":[153],"approaches":[154],"including":[155],"support":[156],"vector":[157],"(SVR),":[159],"single":[160],"layer":[162],"neural":[163,167],"networks":[164,168],"(SHL-NN),":[165],"(THL-NN).":[173],"addition,":[175,201],"can":[179],"obtain":[182],"features":[184],"through":[188],"mapping":[192],"ability,":[193],"which":[194],"effectively":[195],"improves":[196],"precision.":[199],"are":[204],"minimized":[205],"when":[206],"number":[208,234],"reaches":[214],"threshold":[216],"value.":[217],"Above":[218],"number,":[220],"not":[223],"possible":[224],"improve":[226],"accuracy":[229],"further":[231],"increasing":[232],"layers.":[237],"Thus,":[238],"method":[241],"has":[242],"high":[244],"value":[246],"prediction.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
