{"id":"https://openalex.org/W3088961167","doi":"https://doi.org/10.1109/access.2020.3025967","title":"Wind Speed Forecasting Based on Extreme Gradient Boosting","display_name":"Wind Speed Forecasting Based on Extreme Gradient Boosting","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3088961167","doi":"https://doi.org/10.1109/access.2020.3025967","mag":"3088961167"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3025967","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025967","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09203893.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":null,"license_id":null,"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/ielx7/6287639/8948470/09203893.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031602767","display_name":"Cai Ren","orcid":"https://orcid.org/0000-0001-5276-5580"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ren Cai","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075965476","display_name":"Sen Xie","orcid":"https://orcid.org/0000-0002-4074-3998"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Xie","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China","College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-4074-3998","affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072741690","display_name":"Bozhong Wang","orcid":"https://orcid.org/0000-0001-5288-6390"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bozhong Wang","raw_affiliation_strings":["State Grid Hunan Electric Power Corporation Maintenance Company, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-5288-6390","affiliations":[{"raw_affiliation_string":"State Grid Hunan Electric Power Corporation Maintenance Company, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075748919","display_name":"Ruijiang Yang","orcid":"https://orcid.org/0000-0001-6840-5950"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruijiang Yang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-6840-5950","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026835116","display_name":"Daosen Xu","orcid":"https://orcid.org/0000-0001-6236-2988"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daosen Xu","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-6236-2988","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062591328","display_name":"Yang He","orcid":"https://orcid.org/0000-0001-8514-0499"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang He","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-8514-0499","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5031602767"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.1205,"has_fulltext":true,"cited_by_count":71,"citation_normalized_percentile":{"value":0.92283375,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"175063","last_page":"175069"},"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/T10424","display_name":"Electric Power System Optimization","score":0.9901999831199646,"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":0.9843000173568726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.783159613609314},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.7582601308822632},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7316431999206543},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.6651591062545776},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5843851566314697},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5350144505500793},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5094936490058899},{"id":"https://openalex.org/keywords/graphics-processing-unit","display_name":"Graphics processing unit","score":0.4836246073246002},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.4479401707649231},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.43702298402786255},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4226321578025818},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.40241917967796326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3699054718017578},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3286914527416229},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.2649613618850708},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10591739416122437},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08597549796104431}],"concepts":[{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.783159613609314},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.7582601308822632},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7316431999206543},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.6651591062545776},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5843851566314697},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5350144505500793},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5094936490058899},{"id":"https://openalex.org/C2779851693","wikidata":"https://www.wikidata.org/wiki/Q183484","display_name":"Graphics processing unit","level":2,"score":0.4836246073246002},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.4479401707649231},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.43702298402786255},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4226321578025818},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.40241917967796326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3699054718017578},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3286914527416229},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.2649613618850708},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10591739416122437},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08597549796104431},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3025967","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025967","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09203893.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0ba773f953c547bc85669c0f8e5305f3","is_oa":true,"landing_page_url":"https://doaj.org/article/0ba773f953c547bc85669c0f8e5305f3","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 8, Pp 175063-175069 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3025967","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3025967","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09203893.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.9200000166893005,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2408639511","display_name":null,"funder_award_id":"61903257","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3088961167.pdf","grobid_xml":"https://content.openalex.org/works/W3088961167.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W588468042","https://openalex.org/W616486760","https://openalex.org/W1977587074","https://openalex.org/W1979575715","https://openalex.org/W1984061847","https://openalex.org/W1990785420","https://openalex.org/W1993642620","https://openalex.org/W2006161877","https://openalex.org/W2021826571","https://openalex.org/W2024377782","https://openalex.org/W2025037893","https://openalex.org/W2048857692","https://openalex.org/W2057184981","https://openalex.org/W2066341465","https://openalex.org/W2067543652","https://openalex.org/W2070795314","https://openalex.org/W2074715647","https://openalex.org/W2085621130","https://openalex.org/W2090449585","https://openalex.org/W2102303403","https://openalex.org/W2142809749","https://openalex.org/W2149906128","https://openalex.org/W2254535312","https://openalex.org/W2263098707","https://openalex.org/W2295598076","https://openalex.org/W2514536448","https://openalex.org/W2606522347","https://openalex.org/W2608474161","https://openalex.org/W2783448417","https://openalex.org/W2792344217","https://openalex.org/W2821843609","https://openalex.org/W2884380318","https://openalex.org/W2896864326","https://openalex.org/W2897029086","https://openalex.org/W2901078150","https://openalex.org/W2910279921","https://openalex.org/W2914191958","https://openalex.org/W2920974156","https://openalex.org/W2960560113","https://openalex.org/W2963182713","https://openalex.org/W2985419578","https://openalex.org/W2997147307","https://openalex.org/W2999319845","https://openalex.org/W3000471799","https://openalex.org/W3008838724","https://openalex.org/W3021727993","https://openalex.org/W3102476541","https://openalex.org/W3140168516","https://openalex.org/W4251940498","https://openalex.org/W6656476209"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W2913534066","https://openalex.org/W2970375204","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016"],"abstract_inverted_index":{"As":[0],"the":[1,20,28,34,41,45,65,96,105,109,113,120,134,156,161,167],"integration":[2],"of":[3,13,22,36,44,73,104,116,122],"wind":[4,14,24,37,81,117,123],"power":[5,25,124],"into":[6,27,127],"electrical":[7],"energy":[8],"network":[9],"increasing,":[10],"accurate":[11],"forecast":[12,39,83,168],"speed":[15,38,82,118],"becomes":[16],"highly":[17],"important":[18],"in":[19,64,92,138],"case":[21],"large-scale":[23],"connected":[26],"grid.":[29],"In":[30],"order":[31],"to":[32],"improve":[33],"accuracy":[35,169],"and":[40,62,151],"generalization":[42],"ability":[43],"model,":[46],"Extreme":[47,87],"Gradient":[48,88],"Boosting":[49,89],"(XGBoost)":[50],"as":[51,101],"an":[52],"improvement":[53],"from":[54],"gradient":[55],"boosting":[56],"decision":[57],"tree":[58],"(GBDT)":[59],"is":[60,90,99,125],"trained":[61],"deployed":[63],"cheaper":[66],"central":[67],"processing":[68,75],"unit":[69,76],"(CPU)":[70],"devices":[71],"instead":[72],"graphics":[74],"(GPU)":[77],"devices,":[78],"thus,":[79],"a":[80,102],"model":[84,164],"based":[85],"on":[86],"proposed":[91],"this":[93],"paper.":[94],"Firstly,":[95],"historical":[97],"data":[98],"taken":[100],"part":[103],"input":[106],"vectors":[107],"for":[108],"model.":[110],"Moreover,":[111],"considering":[112],"monthly":[114],"change":[115],"characteristics,":[119],"dataset":[121],"divided":[126],"four":[128],"parts":[129],"by":[130,141],"month":[131],"so":[132],"that":[133,160],"models":[135],"are":[136],"constructed":[137],"different":[139],"complexity":[140],"month.":[142],"Finally,":[143],"compared":[144],"with":[145],"back":[146],"propagation":[147],"neural":[148],"networks":[149],"(BPNN)":[150],"linear":[152],"regression":[153],"(LR)":[154],"models,":[155],"experimental":[157],"results":[158],"show":[159],"improved":[162],"XGBoost":[163],"can":[165],"promote":[166],"effectively.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":8}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}