{"id":"https://openalex.org/W2993544948","doi":"https://doi.org/10.1109/access.2019.2957062","title":"Wind Speed Forecasting System Based on the Variational Mode Decomposition Strategy and Immune Selection Multi-Objective Dragonfly Optimization Algorithm","display_name":"Wind Speed Forecasting System Based on the Variational Mode Decomposition Strategy and Immune Selection Multi-Objective Dragonfly Optimization Algorithm","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2993544948","doi":"https://doi.org/10.1109/access.2019.2957062","mag":"2993544948"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2957062","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2957062","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08918258.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/ielx7/6287639/8600701/08918258.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102761442","display_name":"Bo He","orcid":"https://orcid.org/0000-0003-1850-7697"},"institutions":[{"id":"https://openalex.org/I130480701","display_name":"Dongbei University of Finance and Economics","ror":"https://ror.org/05db1pj03","country_code":"CN","type":"education","lineage":["https://openalex.org/I130480701"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Bo","raw_affiliation_strings":["Dongbei University of Finance and Economics Postdoctoral Research Mobile Station, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0003-1850-7697","affiliations":[{"raw_affiliation_string":"Dongbei University of Finance and Economics Postdoctoral Research Mobile Station, Dalian, China","institution_ids":["https://openalex.org/I130480701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044463225","display_name":"Xinsong Niu","orcid":"https://orcid.org/0000-0001-8638-126X"},"institutions":[{"id":"https://openalex.org/I130480701","display_name":"Dongbei University of Finance and Economics","ror":"https://ror.org/05db1pj03","country_code":"CN","type":"education","lineage":["https://openalex.org/I130480701"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinsong Niu","raw_affiliation_strings":["School of Statistics, Dongbei University of Finance and Economics, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0001-8638-126X","affiliations":[{"raw_affiliation_string":"School of Statistics, Dongbei University of Finance and Economics, Dalian, China","institution_ids":["https://openalex.org/I130480701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044720245","display_name":"Jianzhou Wang","orcid":"https://orcid.org/0000-0001-9078-7617"},"institutions":[{"id":"https://openalex.org/I130480701","display_name":"Dongbei University of Finance and Economics","ror":"https://ror.org/05db1pj03","country_code":"CN","type":"education","lineage":["https://openalex.org/I130480701"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhou Wang","raw_affiliation_strings":["School of Statistics, Dongbei University of Finance and Economics, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0001-9078-7617","affiliations":[{"raw_affiliation_string":"School of Statistics, Dongbei University of Finance and Economics, Dalian, China","institution_ids":["https://openalex.org/I130480701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130480701"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.9698,"has_fulltext":true,"cited_by_count":49,"citation_normalized_percentile":{"value":0.94429303,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"178063","last_page":"178081"},"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":0.9855999946594238,"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/T12368","display_name":"Grey System Theory Applications","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6987351179122925},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.6482978463172913},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.6015037298202515},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.5614073872566223},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.531841516494751},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.502964437007904},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.47476768493652344},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4381166994571686},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42069512605667114},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41603463888168335},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3875735402107239},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3526279330253601},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34275177121162415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31007951498031616},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13295981287956238},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12510502338409424}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6987351179122925},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.6482978463172913},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.6015037298202515},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.5614073872566223},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.531841516494751},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.502964437007904},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.47476768493652344},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4381166994571686},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42069512605667114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41603463888168335},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3875735402107239},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3526279330253601},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34275177121162415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31007951498031616},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13295981287956238},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12510502338409424},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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.2019.2957062","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2957062","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08918258.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:b102be21fc604c348be0317970c20941","is_oa":true,"landing_page_url":"https://doaj.org/article/b102be21fc604c348be0317970c20941","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 7, Pp 178063-178081 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2957062","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2957062","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08918258.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":[{"score":0.8799999952316284,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G6935840003","display_name":"\u5927\u89c4\u6a21\u98ce\u7535\u5e76\u7f51\u7ba1\u7406\u4e2d\u7684\u98ce\u80fd\u8d44\u6e90\u8bc4\u4f30\u4e0e\u9884\u6d4b\u7814\u7a76","funder_award_id":"71671029","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7443345334","display_name":null,"funder_award_id":"Grant 71671029","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/W2993544948.pdf","grobid_xml":"https://content.openalex.org/works/W2993544948.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W414544266","https://openalex.org/W1901537671","https://openalex.org/W1964886660","https://openalex.org/W1970392686","https://openalex.org/W1981047607","https://openalex.org/W1983965282","https://openalex.org/W1984061847","https://openalex.org/W2000982976","https://openalex.org/W2022912953","https://openalex.org/W2023685757","https://openalex.org/W2025037893","https://openalex.org/W2036681246","https://openalex.org/W2039238531","https://openalex.org/W2039306928","https://openalex.org/W2051006518","https://openalex.org/W2060606400","https://openalex.org/W2073004501","https://openalex.org/W2080267209","https://openalex.org/W2156250920","https://openalex.org/W2163998921","https://openalex.org/W2329476579","https://openalex.org/W2333175961","https://openalex.org/W2336817976","https://openalex.org/W2463836225","https://openalex.org/W2504266609","https://openalex.org/W2516005877","https://openalex.org/W2560082278","https://openalex.org/W2566017277","https://openalex.org/W2582163918","https://openalex.org/W2599476079","https://openalex.org/W2755132572","https://openalex.org/W2762198305","https://openalex.org/W2763128055","https://openalex.org/W2775477417","https://openalex.org/W2791494608","https://openalex.org/W2883694838","https://openalex.org/W2884415573","https://openalex.org/W2887216976","https://openalex.org/W2891967931","https://openalex.org/W2892055834","https://openalex.org/W2896864326","https://openalex.org/W2897932070","https://openalex.org/W2904796594","https://openalex.org/W2905035404","https://openalex.org/W2907029015","https://openalex.org/W2908908405","https://openalex.org/W2911992235","https://openalex.org/W2912757531","https://openalex.org/W2914856364","https://openalex.org/W2922089800","https://openalex.org/W2925057617","https://openalex.org/W2938204974","https://openalex.org/W2945754770","https://openalex.org/W2946405318","https://openalex.org/W2948535221","https://openalex.org/W2952080445","https://openalex.org/W2960560113","https://openalex.org/W2962708580","https://openalex.org/W2965492561","https://openalex.org/W2975025053","https://openalex.org/W6767804786"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W4380482219","https://openalex.org/W4377969695","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904"],"abstract_inverted_index":{"In":[0,143],"the":[1,4,29,46,49,58,61,103,111,127,132,138,145],"development":[2],"of":[3,32,48,60,105,113],"wind":[5,9,23,33,106,155],"power":[6,156],"industry,":[7],"short-term":[8],"speed":[10,24,107],"forecasting":[11,70],"is":[12,72],"necessary,":[13],"and":[14,51,80,95,117,120,130],"many":[15],"researchers":[16],"have":[17],"made":[18],"substantial":[19],"efforts":[20],"to":[21,84,126],"establish":[22],"prediction":[25,31,41,87,91,122,135,148],"models.":[26],"However,":[27],"realizing":[28],"accurate":[30,86,119],"speeds":[34],"remains":[35],"a":[36,76,151],"challenging":[37],"task.":[38],"The":[39,89],"current":[40],"models":[42,97,140],"do":[43],"not":[44],"consider":[45],"preprocessing":[47,78],"data,":[50],"each":[52],"model":[53,149],"has":[54],"various":[55,114],"shortcomings.":[56],"Considering":[57],"disadvantages":[59],"available":[62],"models,":[63,116],"in":[64,141],"this":[65],"paper,":[66],"an":[67],"advanced":[68],"combined":[69,134,147],"system":[71,92,136],"applied":[73],"that":[74,98],"utilizes":[75],"data":[77],"strategy":[79,83],"parameter":[81],"optimization":[82],"obtain":[85],"values.":[88,123],"proposed":[90,133],"employs":[93],"linear":[94],"nonlinear":[96],"can":[99],"take":[100],"into":[101],"account":[102],"characteristics":[104],"sequences,":[108],"successfully":[109],"combine":[110],"advantages":[112],"single":[115],"yield":[118],"stable":[121],"Finally,":[124],"according":[125],"experimental":[128],"analysis":[129],"discussion,":[131],"outperforms":[137],"compared":[139],"prediction.":[142,157],"conclusion,":[144],"powerful":[146],"provides":[150],"feasible":[152],"scheme":[153],"for":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
