{"id":"https://openalex.org/W2787159342","doi":"https://doi.org/10.1109/la-cci.2017.8285720","title":"Knowledge extraction from time series of electric energy demand using temporal data mining","display_name":"Knowledge extraction from time series of electric energy demand using temporal data mining","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2787159342","doi":"https://doi.org/10.1109/la-cci.2017.8285720","mag":"2787159342"},"language":"en","primary_location":{"id":"doi:10.1109/la-cci.2017.8285720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/la-cci.2017.8285720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","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/A5045045946","display_name":"Alynne Concei\u00e7\u00e3o Saraiva Queiroz","orcid":null},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Alynne C. Saraiva de Queiroz","raw_affiliation_strings":["Programa de Pos-Gradua\u00e7ao em Engenharia El\u00e9trica e de, Computa\u00e7\u00e3o, Universidade Federal do Rio Grande do Norte, Natal, RN, BR"],"affiliations":[{"raw_affiliation_string":"Programa de Pos-Gradua\u00e7ao em Engenharia El\u00e9trica e de, Computa\u00e7\u00e3o, Universidade Federal do Rio Grande do Norte, Natal, RN, BR","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025179228","display_name":"Jos\u00e9 Alfredo Ferreira Costa","orcid":"https://orcid.org/0000-0002-1290-6454"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jose Alfredo F. Costa","raw_affiliation_strings":["Departamento de Engenharia El\u00e9trica, Universidade Federal do Rio Grande do Norte, Natal, RN, BR"],"affiliations":[{"raw_affiliation_string":"Departamento de Engenharia El\u00e9trica, Universidade Federal do Rio Grande do Norte, Natal, RN, BR","institution_ids":["https://openalex.org/I35046152"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045045946"],"corresponding_institution_ids":["https://openalex.org/I35046152"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21327537,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9969000220298767,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9670000076293945,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/metropolitan-area","display_name":"Metropolitan area","score":0.7102763652801514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6328810453414917},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.6099632978439331},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5854925513267517},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.5241725444793701},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.4657942056655884},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4566061496734619},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.4336678087711334},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.432170569896698},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.43161624670028687},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.41301512718200684},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3616095185279846},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.23819303512573242},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2088525891304016},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18265551328659058},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12435096502304077},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.12009575963020325}],"concepts":[{"id":"https://openalex.org/C158739034","wikidata":"https://www.wikidata.org/wiki/Q1907114","display_name":"Metropolitan area","level":2,"score":0.7102763652801514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6328810453414917},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.6099632978439331},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5854925513267517},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.5241725444793701},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.4657942056655884},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4566061496734619},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.4336678087711334},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.432170569896698},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.43161624670028687},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.41301512718200684},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3616095185279846},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.23819303512573242},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2088525891304016},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18265551328659058},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12435096502304077},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.12009575963020325},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/la-cci.2017.8285720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/la-cci.2017.8285720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4000000059604645}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1512654073","https://openalex.org/W1823797891","https://openalex.org/W2017666374","https://openalex.org/W2104557718","https://openalex.org/W2182591763","https://openalex.org/W2185444030","https://openalex.org/W2326172754","https://openalex.org/W4242702158","https://openalex.org/W6686651337"],"related_works":["https://openalex.org/W4212929323","https://openalex.org/W2045046253","https://openalex.org/W2000995042","https://openalex.org/W2494740635","https://openalex.org/W1632599465","https://openalex.org/W1563545158","https://openalex.org/W2115206115","https://openalex.org/W2091545482","https://openalex.org/W3177269507","https://openalex.org/W2379499532"],"abstract_inverted_index":{"Planning":[0],"activities":[1],"are":[2,12],"very":[3],"important":[4],"in":[5,18,46,56,124],"the":[6,10,27,68,104,119,125,131,140,143,150],"energy":[7,62,92],"sector,":[8],"where":[9],"utilities":[11],"seeking":[13],"information":[14],"that":[15,138],"may":[16],"assist":[17,158],"decisions":[19],"regarding":[20],"expansion":[21],"needs":[22],"and":[23,41],"resource":[24],"management,":[25],"improving":[26],"quality":[28],"of":[29,43,53,91,107,121,127,136,142],"their":[30],"services.":[31],"This":[32],"paper":[33],"presents":[34],"a":[35,85,99,155],"methodology":[36],"based":[37],"on":[38],"mining":[39],"tools":[40],"representation":[42],"time":[44,89],"series,":[45],"order":[47],"to":[48,60,157],"extract":[49],"knowledge":[50,137],"from":[51],"series":[52,90],"electricity":[54],"demand":[55,93],"various":[57],"substations":[58,96],"connected":[59],"an":[61],"provider.":[63],"To":[64],"represent":[65],"this":[66],"knowledge,":[67],"language":[69],"proposed":[70,132],"by":[71,98,111],"M\u00f6rchen":[72],"(2005)":[73],"called":[74],"Time":[75],"Series":[76],"Knowledge":[77],"Representation":[78],"(TSKR)":[79],"is":[80],"used.":[81],"It":[82],"was":[83],"conducted":[84],"case":[86],"study":[87],"using":[88],"for":[94,118],"8":[95],"interconnected":[97],"ring":[100],"system,":[101],"which":[102],"feeds":[103],"metropolitan":[105],"area":[106],"Goiania-GO":[108],"(Brazil),":[109],"provided":[110],"CELG":[112],"(Companhia":[113],"Energ\u00e9tica":[114],"de":[115],"Goi\u00e1s),":[116],"responsible":[117],"service":[120],"power":[122],"distribution":[123],"state":[126],"Goi\u00e1s":[128],"(Brazil).":[129],"Using":[130],"methodology,":[133],"three":[134],"levels":[135],"describe":[139],"behavior":[141],"studied":[144],"system":[145,151],"were":[146],"extracted,":[147],"representing":[148],"clearly":[149],"dynamics,":[152],"thus":[153],"becoming":[154],"tool":[156],"planning":[159],"activities.":[160]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
