{"id":"https://openalex.org/W2050529187","doi":"https://doi.org/10.1109/isgteurope.2011.6162721","title":"Hybrid intelligent method of relevant vector machine and regression tree for probabilistic load forecasting","display_name":"Hybrid intelligent method of relevant vector machine and regression tree for probabilistic load forecasting","publication_year":2011,"publication_date":"2011-12-01","ids":{"openalex":"https://openalex.org/W2050529187","doi":"https://doi.org/10.1109/isgteurope.2011.6162721","mag":"2050529187"},"language":"en","primary_location":{"id":"doi:10.1109/isgteurope.2011.6162721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgteurope.2011.6162721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies","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/A5071021361","display_name":"Hatsumi Mori","orcid":null},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"H. Mori","raw_affiliation_strings":["Department of Electronics & Bioinformatics, Meiji University, Kawasaki 214-8571, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electronics & Bioinformatics, Meiji University, Kawasaki 214-8571, Japan","institution_ids":["https://openalex.org/I16656306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074142581","display_name":"Akira Takahashi","orcid":"https://orcid.org/0000-0002-3159-9007"},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"A. Takahashi","raw_affiliation_strings":["Department of Electronics & Bioinformatics, Meiji University, Kawasaki 214-8571, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electronics & Bioinformatics, Meiji University, Kawasaki 214-8571, Japan","institution_ids":["https://openalex.org/I16656306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5071021361"],"corresponding_institution_ids":["https://openalex.org/I16656306"],"apc_list":null,"apc_paid":null,"fwci":1.6197,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.84933998,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9994999766349792,"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":0.9994999766349792,"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/T10320","display_name":"Neural Networks and Applications","score":0.9979000091552734,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7388332486152649},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.679218590259552},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5902679562568665},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5607739686965942},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.515296459197998},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5012412071228027},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4827396273612976},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.46978822350502014},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.43356990814208984},{"id":"https://openalex.org/keywords/relevance-vector-machine","display_name":"Relevance vector machine","score":0.41098207235336304},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40726733207702637},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22743597626686096},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1474352478981018}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7388332486152649},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.679218590259552},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5902679562568665},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5607739686965942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.515296459197998},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5012412071228027},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4827396273612976},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.46978822350502014},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.43356990814208984},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.41098207235336304},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40726733207702637},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22743597626686096},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1474352478981018},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isgteurope.2011.6162721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgteurope.2011.6162721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1567512734","https://openalex.org/W1594031697","https://openalex.org/W1746819321","https://openalex.org/W1869391892","https://openalex.org/W2043752325","https://openalex.org/W2051592850","https://openalex.org/W2067576900","https://openalex.org/W2068059068","https://openalex.org/W2075795701","https://openalex.org/W2075899207","https://openalex.org/W2076768098","https://openalex.org/W2087058869","https://openalex.org/W2095606512","https://openalex.org/W2108423168","https://openalex.org/W2119821739","https://openalex.org/W2148603752","https://openalex.org/W2156909104","https://openalex.org/W2158442843","https://openalex.org/W2167999005","https://openalex.org/W2168138569","https://openalex.org/W2177841694","https://openalex.org/W2330820318","https://openalex.org/W2532814073","https://openalex.org/W2533141911","https://openalex.org/W3085162807","https://openalex.org/W3190219644","https://openalex.org/W4211049957","https://openalex.org/W4239510810","https://openalex.org/W6799072952"],"related_works":["https://openalex.org/W2565312173","https://openalex.org/W2066952721","https://openalex.org/W2335152656","https://openalex.org/W4224922629","https://openalex.org/W3147035969","https://openalex.org/W2359936972","https://openalex.org/W2104936869","https://openalex.org/W2383027800","https://openalex.org/W2206547991","https://openalex.org/W2186666570"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3],"new":[4],"hybrid":[5],"intelligent":[6],"method":[7,28,112],"for":[8],"probabilistic":[9],"short-term":[10],"load":[11],"forecasting":[12],"(STLF)":[13],"in":[14],"power":[15],"systems.":[16],"It":[17,94],"consists":[18],"of":[19,24,36,43,79,104,119],"Relevance":[20],"Vector":[21,86],"Machine":[22,31,87],"(RVM)":[23],"the":[25,40,56,99],"statistical":[26],"learning":[27,50],"called":[29],"Kernel":[30,81],"and":[32,101],"regression":[33],"tree":[34],"(RT)":[35],"data":[37,51,57,61,118],"mining.":[38],"As":[39],"preconditioned":[41],"technique":[42],"data,":[44],"RT":[45],"is":[46,66,77,113],"used":[47],"to":[48,68,89,97,116],"classify":[49],"into":[52,62],"some":[53,63],"clusters":[54],"with":[55,91,107],"similarity.":[58],"After":[59],"classifying":[60],"clusters,":[64],"RVM":[65,76],"constructed":[67],"predict":[69],"one-step":[70],"ahead":[71],"loads":[72],"at":[73],"each":[74],"cluster.":[75],"one":[78],"efficient":[80],"Machines":[82],"that":[83],"extend":[84],"Support":[85],"(SVM)":[88],"deal":[90],"continuous":[92],"variables.":[93],"has":[95],"advantage":[96],"narrow":[98],"lower":[100],"upper":[102],"bounds":[103],"predicted":[105],"values":[106],"high":[108],"accuracy.":[109],"The":[110],"proposed":[111],"successfully":[114],"applied":[115],"real":[117],"Japanese":[120],"utilities.":[121]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}