{"id":"https://openalex.org/W1570245381","doi":"https://doi.org/10.1109/ijcnn.2005.1556396","title":"A hierarchical hybrid neural model with time integrators in long-term peak-load forecasting","display_name":"A hierarchical hybrid neural model with time integrators in long-term peak-load forecasting","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W1570245381","doi":"https://doi.org/10.1109/ijcnn.2005.1556396","mag":"1570245381"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1556396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1556396","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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/A5019696842","display_name":"Ot\u00e1vio A. S. Carpinteiro","orcid":"https://orcid.org/0000-0002-7490-9255"},"institutions":[{"id":"https://openalex.org/I8165072","display_name":"Universidade Federal de Itajub\u00e1","ror":"https://ror.org/00235nr42","country_code":"BR","type":"education","lineage":["https://openalex.org/I8165072"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"O.A.S. Carpinteiro","raw_affiliation_strings":["Research Group on Computer Networks and Software Engineering, Federal University of Itajub\u00e1-UNIFEI, Itajuba, Minas Gerais, Brazil","Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil"],"affiliations":[{"raw_affiliation_string":"Research Group on Computer Networks and Software Engineering, Federal University of Itajub\u00e1-UNIFEI, Itajuba, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I8165072"]},{"raw_affiliation_string":"Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil","institution_ids":["https://openalex.org/I8165072"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038970085","display_name":"Rafael Coradi Leme","orcid":"https://orcid.org/0000-0001-5932-5166"},"institutions":[{"id":"https://openalex.org/I8165072","display_name":"Universidade Federal de Itajub\u00e1","ror":"https://ror.org/00235nr42","country_code":"BR","type":"education","lineage":["https://openalex.org/I8165072"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"R.C. Leme","raw_affiliation_strings":["Research Group on Computer Networks and Software Engineering, Federal University of Itajub\u00e1-UNIFEI, Itajuba, Minas Gerais, Brazil","Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil"],"affiliations":[{"raw_affiliation_string":"Research Group on Computer Networks and Software Engineering, Federal University of Itajub\u00e1-UNIFEI, Itajuba, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I8165072"]},{"raw_affiliation_string":"Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil","institution_ids":["https://openalex.org/I8165072"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069355721","display_name":"Ant\u00f4nio Carlos Zambroni de Souza","orcid":"https://orcid.org/0000-0001-8559-9590"},"institutions":[{"id":"https://openalex.org/I8165072","display_name":"Universidade Federal de Itajub\u00e1","ror":"https://ror.org/00235nr42","country_code":"BR","type":"education","lineage":["https://openalex.org/I8165072"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"A.C. Zambroni de Souza","raw_affiliation_strings":["Research Group on Computer Networks and Software Engineering, Federal University of Itajub\u00e1-UNIFEI, Itajuba, Minas Gerais, Brazil","Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil"],"affiliations":[{"raw_affiliation_string":"Research Group on Computer Networks and Software Engineering, Federal University of Itajub\u00e1-UNIFEI, Itajuba, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I8165072"]},{"raw_affiliation_string":"Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil","institution_ids":["https://openalex.org/I8165072"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5098282463","display_name":"P.S. Quintanilha","orcid":null},"institutions":[{"id":"https://openalex.org/I8165072","display_name":"Universidade Federal de Itajub\u00e1","ror":"https://ror.org/00235nr42","country_code":"BR","type":"education","lineage":["https://openalex.org/I8165072"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"P.S. Quintanilha","raw_affiliation_strings":["Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil"],"affiliations":[{"raw_affiliation_string":"Res. Group on Comput. Networks & Software Eng., Fed. Univ. of Itajuba, Brazil","institution_ids":["https://openalex.org/I8165072"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019696842"],"corresponding_institution_ids":["https://openalex.org/I8165072"],"apc_list":null,"apc_paid":null,"fwci":1.8435,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.79730311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"5","issue":null,"first_page":"2960","last_page":"2965"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9970999956130981,"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":0.9922000169754028,"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/perceptron","display_name":"Perceptron","score":0.7189323306083679},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7130992412567139},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6876986026763916},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6611329913139343},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.6554783582687378},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.6105353236198425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5059050917625427},{"id":"https://openalex.org/keywords/integrator","display_name":"Integrator","score":0.505420446395874},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.5029615759849548},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40822240710258484},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3273446559906006}],"concepts":[{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.7189323306083679},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7130992412567139},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6876986026763916},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6611329913139343},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6554783582687378},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.6105353236198425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5059050917625427},{"id":"https://openalex.org/C79518650","wikidata":"https://www.wikidata.org/wiki/Q2081431","display_name":"Integrator","level":3,"score":0.505420446395874},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.5029615759849548},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40822240710258484},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3273446559906006},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2005.1556396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1556396","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W43942032","https://openalex.org/W118919422","https://openalex.org/W1535810436","https://openalex.org/W1599613776","https://openalex.org/W1899402344","https://openalex.org/W2019385508","https://openalex.org/W2031520589","https://openalex.org/W2040598998","https://openalex.org/W2048665112","https://openalex.org/W2107025615","https://openalex.org/W2122936683","https://openalex.org/W2124581141","https://openalex.org/W2128808037","https://openalex.org/W2136451213","https://openalex.org/W2146097858","https://openalex.org/W2151767444","https://openalex.org/W4245176872","https://openalex.org/W4252589412","https://openalex.org/W6604775208","https://openalex.org/W6632223199","https://openalex.org/W6678265029"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W2523437662","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2766585573","https://openalex.org/W4387490624","https://openalex.org/W4286643620"],"abstract_inverted_index":{"A":[0],"novel":[1],"hierarchical":[2,69],"hybrid":[3],"neural":[4,19],"model":[5,20,60],"to":[6,63,91],"the":[7,34,48,68,71,101,105,116],"problem":[8],"of":[9,24,33],"long-term":[10],"peak-load":[11,103],"forecasting":[12],"is":[13,21,61],"proposed":[14],"in":[15,46,115],"this":[16],"paper.":[17,117],"The":[18,59,109],"made":[22],"up":[23],"two":[25,107],"self-organizing":[26],"map":[27],"nets":[28],"-":[29],"one":[30],"on":[31,79],"top":[32],"other":[35],"-,":[36],"and":[37,70,77,113],"a":[38,56,64,84],"single-layer":[39],"perceptron.":[40,66],"It":[41],"has":[42],"application":[43],"into":[44],"domains":[45],"which":[47],"context":[49],"information":[50],"given":[51],"by":[52],"former":[53],"events":[54],"plays":[55],"primary":[57],"role.":[58],"compared":[62],"multilayer":[65,72],"Both":[67],"perceptron":[73],"models":[74],"are":[75,89,111],"trained":[76],"assessed":[78],"load":[80],"data":[81],"extracted":[82],"from":[83],"North-American":[85],"electric":[86,102],"utility.":[87],"They":[88],"required":[90],"predict":[92],"either":[93],"once":[94,98],"every":[95,99],"week":[96],"or":[97],"month":[100],"during":[104],"next":[106],"years.":[108],"results":[110],"presented":[112],"evaluated":[114]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}