{"id":"https://openalex.org/W4213109121","doi":"https://doi.org/10.1145/3503823.3503827","title":"Use of Artificial Neural Networks for Short Term Load Forecasting","display_name":"Use of Artificial Neural Networks for Short Term Load Forecasting","publication_year":2021,"publication_date":"2021-11-26","ids":{"openalex":"https://openalex.org/W4213109121","doi":"https://doi.org/10.1145/3503823.3503827"},"language":"en","primary_location":{"id":"doi:10.1145/3503823.3503827","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503823.3503827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"25th Pan-Hellenic Conference on Informatics","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/A5026546820","display_name":"Athanasios Ioannis Arvanitidis","orcid":"https://orcid.org/0000-0002-6547-7454"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Athanasios Ioannis Arvanitidis","raw_affiliation_strings":["Electrical and Computer Engineering, University of Thessaly, Greece"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Thessaly, Greece","institution_ids":["https://openalex.org/I145722265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017449784","display_name":"Dimitrios Bargiotas","orcid":"https://orcid.org/0000-0001-8285-8972"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitrios Bargiotas","raw_affiliation_strings":["Electrical and Computer Engineering, University of Thessaly, Greece"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Thessaly, Greece","institution_ids":["https://openalex.org/I145722265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026546820"],"corresponding_institution_ids":["https://openalex.org/I145722265"],"apc_list":null,"apc_paid":null,"fwci":0.4048,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62367684,"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":"18","last_page":"22"},"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/T10573","display_name":"Power Quality and Harmonics","score":0.9909999966621399,"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/T10424","display_name":"Electric Power System Optimization","score":0.989799976348877,"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/computer-science","display_name":"Computer science","score":0.739561915397644},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6971403360366821},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.6212653517723083},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.6013324856758118},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.5737719535827637},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5476967692375183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5381655693054199},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4602254033088684},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4529215395450592},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42864513397216797},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.39357075095176697},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.3698670268058777},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.34862372279167175},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21894389390945435}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.739561915397644},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6971403360366821},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.6212653517723083},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6013324856758118},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.5737719535827637},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5476967692375183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5381655693054199},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4602254033088684},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4529215395450592},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42864513397216797},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.39357075095176697},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3698670268058777},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.34862372279167175},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21894389390945435},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3503823.3503827","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503823.3503827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"25th Pan-Hellenic Conference on Informatics","raw_type":"proceedings-article"},{"id":"pmh:oai:ir.lib.uth.gr:11615/70830","is_oa":false,"landing_page_url":"http://hdl.handle.net/11615/70830","pdf_url":null,"source":{"id":"https://openalex.org/S4306400243","display_name":"University of Thessaly Institutional Repository (University of Thessaly)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145722265","host_organization_name":"University of Thessaly","host_organization_lineage":["https://openalex.org/I145722265"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ACM International Conference Proceeding Series","raw_type":"conferenceItem"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1888309248","https://openalex.org/W1899402344","https://openalex.org/W2002016471","https://openalex.org/W2010721786","https://openalex.org/W2028070629","https://openalex.org/W2079046445","https://openalex.org/W2088023283","https://openalex.org/W2120046447","https://openalex.org/W2162641381","https://openalex.org/W2169548144","https://openalex.org/W2248484948","https://openalex.org/W2282356154","https://openalex.org/W2522450402","https://openalex.org/W2790545079","https://openalex.org/W2889256874","https://openalex.org/W3016462725","https://openalex.org/W4213316061"],"related_works":["https://openalex.org/W2082756648","https://openalex.org/W2804364458","https://openalex.org/W3194278305","https://openalex.org/W4298130764","https://openalex.org/W2289648981","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W2083665254","https://openalex.org/W2393816671"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,23,121,128],"schedule":[3],"an":[4,12,60,136],"effective":[5],"service":[6],"and":[7,44,53,106,124],"economical":[8],"capital":[9],"extension":[10],"of":[11,37,41,55,62,80,85],"electric":[13],"power":[14,28,42],"distribution":[15],"system,":[16],"the":[17,25,38,78],"system":[18],"administrator":[19],"must":[20],"be":[21,118],"able":[22],"predict":[24],"need":[26],"for":[27,50,92],"delivery.":[29],"Short":[30],"Term":[31],"Load":[32],"Forecasting":[33],"(STLF)":[34],"is":[35,48,94],"one":[36],"critical":[39],"topics":[40],"systems":[43],"precise":[45],"load":[46],"forecasting":[47],"crucial":[49],"controlling":[51],"supply":[52],"demand":[54],"electricity.":[56],"This":[57],"paper":[58],"provides":[59],"overview":[61],"innovative":[63],"methods":[64],"based":[65,99],"on":[66,100],"Artificial":[67],"Neural":[68],"Networks":[69,104],"(ANNs),":[70],"as":[71,73,115],"well":[72],"their":[74,107],"current":[75],"use":[76],"in":[77,88,135],"field":[79],"STLF.":[81],"A":[82],"short":[83],"review":[84],"researchers\u2019":[86],"work":[87],"Multilayer":[89],"Perceptron":[90],"(MLP)":[91],"STLF":[93],"presented.":[95],"An":[96],"improved":[97,139],"confrontation":[98],"Radial":[101],"Basis":[102],"Function":[103],"(RBFNs)":[105],"advantages":[108],"are":[109],"examined.":[110],"Different":[111],"optimization":[112],"techniques,":[113],"such":[114],"clustering,":[116],"can":[117],"used":[119],"whether":[120],"reduce":[122],"errors":[123],"its":[125],"variations":[126],"or":[127],"speed":[129],"up":[130],"computational":[131],"time,":[132],"hence":[133],"resulting":[134],"even":[137],"more":[138],"model.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}