{"id":"https://openalex.org/W2007094681","doi":"https://doi.org/10.1109/icmlc.2013.6890363","title":"SVM with improved grid search and its application to wind power prediction","display_name":"SVM with improved grid search and its application to wind power prediction","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2007094681","doi":"https://doi.org/10.1109/icmlc.2013.6890363","mag":"2007094681"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2013.6890363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2013.6890363","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Machine Learning and Cybernetics","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/A5100755576","display_name":"Meng Li","orcid":"https://orcid.org/0000-0001-8399-8483"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Meng","raw_affiliation_strings":["North China Electric Power University, Baoding, China","North China Electric Power University,Baoding,071003,China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"North China Electric Power University,Baoding,071003,China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108576016","display_name":"Jinwei Shi","orcid":"https://orcid.org/0009-0004-7850-488X"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin-Wei Shi","raw_affiliation_strings":["North China Electric Power University, Baoding, China","North China Electric Power University,Baoding,071003,China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"North China Electric Power University,Baoding,071003,China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080102032","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0001-7594-7387"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["North China Electric Power University, Baoding, China","North China Electric Power University,Baoding,071003,China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"North China Electric Power University,Baoding,071003,China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023607243","display_name":"Xiaoqiang Wen","orcid":"https://orcid.org/0000-0001-9897-4994"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Qiang Wen","raw_affiliation_strings":["North China Electric Power University, Baoding, China","North China Electric Power University,Baoding,071003,China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"North China Electric Power University,Baoding,071003,China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100755576"],"corresponding_institution_ids":["https://openalex.org/I153473198"],"apc_list":null,"apc_paid":null,"fwci":0.2364,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.58971645,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T14444","display_name":"Power Systems and Renewable Energy","score":0.9916999936103821,"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"}},{"id":"https://openalex.org/T12451","display_name":"Smart Grid and Power Systems","score":0.9898999929428101,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6440421342849731},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.613995373249054},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6123207807540894},{"id":"https://openalex.org/keywords/power-grid","display_name":"Power grid","score":0.5083698630332947},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.463808536529541},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.40817147493362427},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35029420256614685},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14251494407653809},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.14122948050498962},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11972317099571228}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6440421342849731},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.613995373249054},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6123207807540894},{"id":"https://openalex.org/C2983254600","wikidata":"https://www.wikidata.org/wiki/Q1096907","display_name":"Power grid","level":3,"score":0.5083698630332947},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.463808536529541},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.40817147493362427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35029420256614685},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14251494407653809},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.14122948050498962},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11972317099571228},{"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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2013.6890363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2013.6890363","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9100000262260437}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1984703120","https://openalex.org/W2038105731","https://openalex.org/W2111307099","https://openalex.org/W2143703772","https://openalex.org/W2165537555","https://openalex.org/W2165799067","https://openalex.org/W2318041010","https://openalex.org/W2351379083","https://openalex.org/W2357654205","https://openalex.org/W2358256409","https://openalex.org/W2359174239","https://openalex.org/W2360038409","https://openalex.org/W2361765050","https://openalex.org/W2362973603","https://openalex.org/W2363920117","https://openalex.org/W2366786103","https://openalex.org/W2373384809","https://openalex.org/W2374224384","https://openalex.org/W2376335838","https://openalex.org/W2387940658","https://openalex.org/W2388247048","https://openalex.org/W2388498011","https://openalex.org/W3215652986","https://openalex.org/W7071499899"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W1980100242","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W4315815996"],"abstract_inverted_index":{"Wind":[0],"power":[1,15,22,40,148,176],"prediction":[2,23,28,41,84,149],"is":[3,24,63,103,170],"of":[4,13,20,27,54,83,109,120],"great":[5],"significance":[6],"to":[7,50,65,79,99,105],"the":[8,14,25,38,52,67,81,91,107,110,121,129,151,157,166],"safe":[9],"and":[10,43,56,73,125,138,153,169],"stable":[11],"operation":[12],"system.":[16],"The":[17,61,86],"key":[18],"factor":[19],"wind":[21,39,71,175],"selection":[26],"model.":[29,60],"This":[30],"paper":[31],"chooses":[32],"support":[33],"vector":[34],"machine":[35],"(SVM)":[36],"as":[37],"model":[42,62,92,112,123,159],"applies":[44],"an":[45],"improved":[46,115,162],"grid":[47,116,163],"search":[48,117,164],"method":[49],"optimize":[51],"parameters":[53],"C":[55],"g":[57],"in":[58,150,174],"SVM":[59,111,122,158],"able":[64],"predict":[66],"real-time":[68],"(15":[69],"minutes)":[70],"power,":[72],"several":[74],"evaluation":[75],"indicators":[76],"are":[77],"used":[78,104,146],"analyze":[80],"accuracy":[82,95,168],"results.":[85],"simulation":[87],"results":[88,126,154],"show":[89,127,155],"that":[90,119,128,156],"has":[93],"good":[94],"which":[96],"reaches":[97],"up":[98],"78.49%.":[100],"An":[101],"experiment":[102],"compare":[106],"performance":[108],"based":[113,160],"on":[114,161],"with":[118],"only,":[124],"former":[130],"performs":[131],"better.":[132],"For":[133],"comparative":[134],"analysis,":[135],"time":[136],"series":[137],"Back":[139],"Propagation":[140],"(BP)":[141],"neural":[142],"network":[143],"were":[144],"also":[145],"for":[147],"paper,":[152],"gets":[165],"highest":[167],"a":[171],"useful":[172],"tool":[173],"prediction.":[177]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}