{"id":"https://openalex.org/W3190090439","doi":"https://doi.org/10.1109/cec45853.2021.9504754","title":"Evolutionary Ensemble Learning Using Multimodal Multi-objective Optimization Algorithm Based on Grid for Wind Speed Forecasting","display_name":"Evolutionary Ensemble Learning Using Multimodal Multi-objective Optimization Algorithm Based on Grid for Wind Speed Forecasting","publication_year":2021,"publication_date":"2021-06-28","ids":{"openalex":"https://openalex.org/W3190090439","doi":"https://doi.org/10.1109/cec45853.2021.9504754","mag":"3190090439"},"language":"en","primary_location":{"id":"doi:10.1109/cec45853.2021.9504754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec45853.2021.9504754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Congress on Evolutionary Computation (CEC)","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/A5101631295","display_name":"Yi Hu","orcid":"https://orcid.org/0000-0002-0873-1436"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Hu","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100676081","display_name":"Jing Liang","orcid":"https://orcid.org/0000-0003-0811-0223"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Liang","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001242154","display_name":"Boyang Qu","orcid":"https://orcid.org/0000-0001-7539-3927"},"institutions":[{"id":"https://openalex.org/I132586189","display_name":"Zhongyuan University of Technology","ror":"https://ror.org/0360zcg91","country_code":"CN","type":"education","lineage":["https://openalex.org/I132586189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyang Qu","raw_affiliation_strings":["School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I132586189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100739253","display_name":"Jie Wang","orcid":"https://orcid.org/0000-0002-6160-5164"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100413391","display_name":"Yanli Wang","orcid":"https://orcid.org/0000-0003-4247-7352"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanli Wang","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047187615","display_name":"Panpan Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Panpan Wei","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2034,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51077659,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1727","last_page":"1734"},"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/T10424","display_name":"Electric Power System Optimization","score":0.994700014591217,"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":0.9805999994277954,"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/wind-speed","display_name":"Wind speed","score":0.7299258708953857},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.729381799697876},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7291639447212219},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.7237769961357117},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.5798012614250183},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.5417985320091248},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5354305505752563},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5333753824234009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5067620873451233},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.4816702604293823},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4473419189453125},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42215585708618164},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36072081327438354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1195107102394104},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07642292976379395},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.07527130842208862}],"concepts":[{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.7299258708953857},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.729381799697876},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7291639447212219},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7237769961357117},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.5798012614250183},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5417985320091248},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5354305505752563},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5333753824234009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5067620873451233},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.4816702604293823},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4473419189453125},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42215585708618164},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36072081327438354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1195107102394104},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07642292976379395},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.07527130842208862},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec45853.2021.9504754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec45853.2021.9504754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322770","display_name":"Foundation of Henan Educational Committee","ror":"https://ror.org/00xvf9d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1966080284","https://openalex.org/W1969988238","https://openalex.org/W1973048907","https://openalex.org/W1998559503","https://openalex.org/W2004670864","https://openalex.org/W2050038283","https://openalex.org/W2071694551","https://openalex.org/W2083620425","https://openalex.org/W2125056386","https://openalex.org/W2126105956","https://openalex.org/W2128357515","https://openalex.org/W2229668941","https://openalex.org/W2329476579","https://openalex.org/W2343601797","https://openalex.org/W2345888804","https://openalex.org/W2510493362","https://openalex.org/W2544046091","https://openalex.org/W2558610617","https://openalex.org/W2573526403","https://openalex.org/W2792578766","https://openalex.org/W2899276225","https://openalex.org/W2947137854","https://openalex.org/W2965492561","https://openalex.org/W2968688008","https://openalex.org/W2979640675","https://openalex.org/W3104757324","https://openalex.org/W3122213170","https://openalex.org/W3125918112","https://openalex.org/W6641799410"],"related_works":["https://openalex.org/W2944292463","https://openalex.org/W3014252901","https://openalex.org/W2188759683","https://openalex.org/W2794896638","https://openalex.org/W4317376680","https://openalex.org/W4360777922","https://openalex.org/W2891633941","https://openalex.org/W3208169454","https://openalex.org/W4390905871","https://openalex.org/W3202800081"],"abstract_inverted_index":{"Improving":[0],"the":[1,10,51,69,83,86],"accuracy":[2],"of":[3,12,26,60,85],"wind":[4,13,75,91],"speed":[5,76,92],"forecasting":[6,77],"is":[7,56],"essential":[8],"for":[9],"usage":[11],"energy.":[14],"This":[15],"paper":[16],"proposes":[17],"an":[18],"evolutionary":[19,45],"ensemble":[20,27,39,53],"learning":[21,54],"(EEL)":[22],"method,":[23],"which":[24],"consists":[25],"empirical":[28],"mode":[29],"decomposition":[30],"(EEMD),":[31],"random":[32],"vector":[33],"functional":[34],"link":[35],"network":[36],"(RVFL)":[37],"based":[38],"learning,":[40],"and":[41],"grid-based":[42],"multimodal":[43],"multi-objective":[44],"algorithm":[46],"(MMOG).":[47],"Based":[48],"on":[49,73],"MMOG,":[50],"proposed":[52,70,87],"model":[55,72,89],"improved":[57],"in":[58,90],"terms":[59],"accuracy.":[61],"Several":[62],"benchmark":[63],"forecast":[64],"methods":[65],"are":[66],"compared":[67],"with":[68],"EEL":[71,88],"12":[74],"datasets.":[78],"The":[79],"experiment":[80],"results":[81],"validate":[82],"superiority":[84],"forecasting.":[93]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}