{"id":"https://openalex.org/W2765297235","doi":"https://doi.org/10.1109/isgt.2017.8086043","title":"Recurrent neural network based user classification for smart grids","display_name":"Recurrent neural network based user classification for smart grids","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2765297235","doi":"https://doi.org/10.1109/isgt.2017.8086043","mag":"2765297235"},"language":"en","primary_location":{"id":"doi:10.1109/isgt.2017.8086043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt.2017.8086043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Power &amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)","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/A5010807777","display_name":"K\u00e1lm\u00e1n Tornai","orcid":"https://orcid.org/0000-0003-1852-0816"},"institutions":[{"id":"https://openalex.org/I31882830","display_name":"P\u00e1zm\u00e1ny P\u00e9ter Catholic University","ror":"https://ror.org/05v9kya57","country_code":"HU","type":"education","lineage":["https://openalex.org/I31882830"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Kalman Tornai","raw_affiliation_strings":["P&#x00E1;zm&#x00E1;ny P&#x00E9;ter Catholic University, Faculty of Information Technology and Bionics, Budapest, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"P&#x00E1;zm&#x00E1;ny P&#x00E9;ter Catholic University, Faculty of Information Technology and Bionics, Budapest, Hungary","institution_ids":["https://openalex.org/I31882830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037792885","display_name":"Andr\u00e1s Ol\u00e1h","orcid":"https://orcid.org/0009-0003-4796-8932"},"institutions":[{"id":"https://openalex.org/I31882830","display_name":"P\u00e1zm\u00e1ny P\u00e9ter Catholic University","ror":"https://ror.org/05v9kya57","country_code":"HU","type":"education","lineage":["https://openalex.org/I31882830"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Andr\u00e1s Ol\u00e1h","raw_affiliation_strings":["P&#x00E1;zm&#x00E1;ny P&#x00E9;ter Catholic University, Faculty of Information Technology and Bionics, Budapest, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"P&#x00E1;zm&#x00E1;ny P&#x00E9;ter Catholic University, Faculty of Information Technology and Bionics, Budapest, Hungary","institution_ids":["https://openalex.org/I31882830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067417030","display_name":"Rajmund Drenyovszki","orcid":"https://orcid.org/0000-0002-9462-2729"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rajmund Drenyovszki","raw_affiliation_strings":["Pallas Athene University, GAMF Faculty of Engineering and Computer Science, Kecskemet, Hungary","GAMF Faculty of Engineering and Computer Science, Pallas Athene University, Kecskemet, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pallas Athene University, GAMF Faculty of Engineering and Computer Science, Kecskemet, Hungary","institution_ids":[]},{"raw_affiliation_string":"GAMF Faculty of Engineering and Computer Science, Pallas Athene University, Kecskemet, Hungary","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029933708","display_name":"L\u00f3r\u00e1nt Kov\u00e1cs","orcid":"https://orcid.org/0000-0001-9930-348X"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"L\u00f3r\u00e1nt Kov\u00e1cs","raw_affiliation_strings":["Pallas Athene University, GAMF Faculty of Engineering and Computer Science, Kecskemet, Hungary","Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pallas Athene University, GAMF Faculty of Engineering and Computer Science, Kecskemet, Hungary","institution_ids":[]},{"raw_affiliation_string":"Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098429562","display_name":"Istv\u00e1n Pint\u00e9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Istv\u00e1n Pint\u00e9","raw_affiliation_strings":["Pallas Athene University, GAMF Faculty of Engineering and Computer Science, Kecskemet, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pallas Athene University, GAMF Faculty of Engineering and Computer Science, Kecskemet, Hungary","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046057044","display_name":"J\u00e1nos Levendovszky","orcid":"https://orcid.org/0000-0003-1406-442X"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Janos Levendovszky","raw_affiliation_strings":["Budapest University of Technology and Economics, Department of Networked Systems and Services, Budapest, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics, Department of Networked Systems and Services, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0233,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.78840863,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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/T10603","display_name":"Smart Grid Energy Management","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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7843140363693237},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.652079164981842},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5805018544197083},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5621140599250793},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5573004484176636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5567225217819214},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.5301716327667236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5278947949409485},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4598797559738159},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.4329605996608734},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1203550398349762}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7843140363693237},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.652079164981842},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5805018544197083},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5621140599250793},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5573004484176636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5567225217819214},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.5301716327667236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5278947949409485},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4598797559738159},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.4329605996608734},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1203550398349762},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isgt.2017.8086043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt.2017.8086043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Power &amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1997102766","https://openalex.org/W1998238819","https://openalex.org/W2002011878","https://openalex.org/W2030846484","https://openalex.org/W2107425660","https://openalex.org/W2111426715","https://openalex.org/W2117688906","https://openalex.org/W2124776405","https://openalex.org/W2141278204","https://openalex.org/W2152283452","https://openalex.org/W2161078209","https://openalex.org/W2509484269","https://openalex.org/W2517621268","https://openalex.org/W4205930639","https://openalex.org/W4285719527","https://openalex.org/W6676236601"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W1969219540","https://openalex.org/W2143413548","https://openalex.org/W2370459448","https://openalex.org/W2105067402"],"abstract_inverted_index":{"Power":[0],"consuming":[1],"users":[2],"and":[3,16,28],"buildings":[4],"with":[5,13,22,130],"different":[6,14,23],"power":[7,36,45,53,137],"consumption":[8,87,138],"patterns":[9],"may":[10],"be":[11,18,58,62],"treated":[12],"conditions":[15],"can":[17,57,61,150],"taken":[19],"into":[20],"consideration":[21],"parameters":[24],"during":[25],"capacity":[26],"planning":[27],"distribution.":[29],"Thus":[30],"the":[31,49,78,86,98,112,121,158],"automated,":[32],"unsupervised":[33],"categorization":[34],"of":[35,43,52,77,114],"consumers":[37,54,115],"is":[38,69,85,163],"a":[39],"very":[40],"important":[41,71],"task":[42,72],"smart":[44],"transmission":[46],"systems.":[47],"Knowing":[48],"behavioral":[50],"categories":[51],"better":[55,65],"models":[56],"created":[59],"which":[60,68,91],"used":[63],"for":[64,73,82,101],"behavior":[66],"forecast":[67,88,94,122],"an":[70],"load":[74],"balancing.":[75],"One":[76],"existing":[79,131,152],"best":[80],"solutions":[81],"consumer":[83,143],"classification":[84,113,124,132,144],"based":[89,123],"scheme":[90],"applies":[92],"nonlinear":[93],"techniques":[95],"to":[96,165],"determine":[97],"class":[99,160],"assignment":[100,161],"new":[102,109],"consumers.":[103],"In":[104],"this":[105],"paper,":[106],"we":[107],"present":[108],"results":[110,127],"on":[111],"using":[116,134],"recurrent":[117,147],"neural":[118,148],"networks":[119,149],"in":[120,155],"framework.":[125],"The":[126],"are":[128],"compared":[129],"methods":[133,153],"real,":[135],"measured":[136],"data.":[139],"We":[140],"demonstrate":[141],"that":[142],"performed":[145],"by":[146],"outperform":[151],"as":[154],"several":[156],"cases":[157],"correct":[159],"rate":[162],"near":[164],"100%.":[166]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
