{"id":"https://openalex.org/W2792253101","doi":"https://doi.org/10.1109/tsg.2018.2807845","title":"Probabilistic Load Forecasting Using an Improved Wavelet Neural Network Trained by Generalized Extreme Learning Machine","display_name":"Probabilistic Load Forecasting Using an Improved Wavelet Neural Network Trained by Generalized Extreme Learning Machine","publication_year":2018,"publication_date":"2018-02-21","ids":{"openalex":"https://openalex.org/W2792253101","doi":"https://doi.org/10.1109/tsg.2018.2807845","mag":"2792253101"},"language":"en","primary_location":{"id":"doi:10.1109/tsg.2018.2807845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2018.2807845","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/11250/2586349","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015035499","display_name":"Mehdi Rafiei","orcid":"https://orcid.org/0000-0002-3708-6173"},"institutions":[{"id":"https://openalex.org/I204490172","display_name":"Shiraz University of Technology","ror":"https://ror.org/04bxa3v83","country_code":"IR","type":"education","lineage":["https://openalex.org/I204490172"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mehdi Rafiei","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran","institution_ids":["https://openalex.org/I204490172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079822116","display_name":"Taher Niknam","orcid":"https://orcid.org/0000-0002-9391-6901"},"institutions":[{"id":"https://openalex.org/I204490172","display_name":"Shiraz University of Technology","ror":"https://ror.org/04bxa3v83","country_code":"IR","type":"education","lineage":["https://openalex.org/I204490172"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Taher Niknam","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran"],"raw_orcid":"https://orcid.org/0000-0002-9391-6901","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran","institution_ids":["https://openalex.org/I204490172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044090625","display_name":"Jamshid Aghaei","orcid":"https://orcid.org/0000-0002-5254-9148"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Jamshid Aghaei","raw_affiliation_strings":["Department of Electric Power Engineering, Norwegian University of Science and Technology, Trondheim, Norway"],"raw_orcid":"https://orcid.org/0000-0002-5254-9148","affiliations":[{"raw_affiliation_string":"Department of Electric Power Engineering, Norwegian University of Science and Technology, Trondheim, Norway","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088560163","display_name":"Miadreza Shafie\u2010khah","orcid":"https://orcid.org/0000-0003-1691-5355"},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Miadreza Shafie-Khah","raw_affiliation_strings":["C-MAST, University of Beira Interior, Covilh\u00e3, Portugal"],"raw_orcid":"https://orcid.org/0000-0003-1691-5355","affiliations":[{"raw_affiliation_string":"C-MAST, University of Beira Interior, Covilh\u00e3, Portugal","institution_ids":["https://openalex.org/I161321875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065382518","display_name":"Jo\u00e3o P. S. Catal\u00e0o","orcid":"https://orcid.org/0000-0002-2105-3051"},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Joao P. S. Catalao","raw_affiliation_strings":["C-MAST, University of Beira Interior, Covilh\u00e3, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-2105-3051","affiliations":[{"raw_affiliation_string":"C-MAST, University of Beira Interior, Covilh\u00e3, Portugal","institution_ids":["https://openalex.org/I161321875"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.4867,"has_fulltext":false,"cited_by_count":168,"citation_normalized_percentile":{"value":0.99173539,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"9","issue":"6","first_page":"6961","last_page":"6971"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9997000098228455,"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/T10424","display_name":"Electric Power System Optimization","score":0.9957000017166138,"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":0.6799622178077698},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6746729016304016},{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"Probabilistic forecasting","score":0.6720385551452637},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5602589845657349},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.5302754640579224},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.512535810470581},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4796026945114136},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.470463365316391},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.453232079744339},{"id":"https://openalex.org/keywords/electricity-market","display_name":"Electricity market","score":0.44263696670532227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43856093287467957},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4139617681503296},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.413326621055603},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.38259732723236084},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.370286762714386},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2569555938243866},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.1783871054649353},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08272981643676758}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6799622178077698},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6746729016304016},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.6720385551452637},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5602589845657349},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.5302754640579224},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.512535810470581},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4796026945114136},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.470463365316391},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.453232079744339},{"id":"https://openalex.org/C146733006","wikidata":"https://www.wikidata.org/wiki/Q676081","display_name":"Electricity market","level":3,"score":0.44263696670532227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43856093287467957},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4139617681503296},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.413326621055603},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.38259732723236084},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.370286762714386},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2569555938243866},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.1783871054649353},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08272981643676758},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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":2,"locations":[{"id":"doi:10.1109/tsg.2018.2807845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2018.2807845","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-article"},{"id":"pmh:oai:brage.bibsys.no:11250/2586349","is_oa":true,"landing_page_url":"http://hdl.handle.net/11250/2586349","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"6961-6971","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:brage.bibsys.no:11250/2586349","is_oa":true,"landing_page_url":"http://hdl.handle.net/11250/2586349","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"6961-6971","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1565746575","https://openalex.org/W1599806358","https://openalex.org/W2019949418","https://openalex.org/W2025478210","https://openalex.org/W2039346833","https://openalex.org/W2069722134","https://openalex.org/W2074911163","https://openalex.org/W2076163358","https://openalex.org/W2083172453","https://openalex.org/W2111072639","https://openalex.org/W2117897510","https://openalex.org/W2126709108","https://openalex.org/W2129651074","https://openalex.org/W2134603844","https://openalex.org/W2136382126","https://openalex.org/W2150783679","https://openalex.org/W2158238776","https://openalex.org/W2159613153","https://openalex.org/W2202089267","https://openalex.org/W2209764198","https://openalex.org/W2275088575","https://openalex.org/W2286305802","https://openalex.org/W2296948037","https://openalex.org/W2300781102","https://openalex.org/W2333670465","https://openalex.org/W2342050018","https://openalex.org/W2490223215","https://openalex.org/W2527129049","https://openalex.org/W2527136714","https://openalex.org/W2597866042","https://openalex.org/W4244777963","https://openalex.org/W6636253261","https://openalex.org/W6679935922"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W1534274833","https://openalex.org/W31566076","https://openalex.org/W3117246195","https://openalex.org/W2081850291","https://openalex.org/W156620619","https://openalex.org/W2914363205","https://openalex.org/W1598221548","https://openalex.org/W2810726137","https://openalex.org/W3178643251"],"abstract_inverted_index":{"Competitive":[0],"transactions":[1],"resulting":[2],"from":[3],"recent":[4],"restructuring":[5],"of":[6,34,73,105,136],"the":[7,56,59,71,74,77,85,91,103,124,130,137],"electricity":[8,36,95],"market,":[9],"have":[10],"made":[11],"achieving":[12],"a":[13,30],"precise":[14],"and":[15,53,62,93,108,114,134],"reliable":[16],"load":[17,21,37,78],"forecasting,":[18,22,38],"especially":[19],"probabilistic":[20,35,79],"an":[23,46],"important":[24],"topic.":[25],"Hence,":[26],"this":[27],"paper":[28],"presents":[29],"novel":[31],"hybrid":[32],"method":[33],"including":[39],"generalized":[40],"extreme":[41],"learning":[42],"machine":[43],"for":[44],"training":[45],"improved":[47],"wavelet":[48,51],"neural":[49],"network,":[50],"preprocessing":[52],"bootstrapping.":[54],"In":[55,81],"proposed":[57,125,138],"method,":[58,86],"forecasting":[60],"model":[61,75,106],"data":[63,109],"noise":[64],"uncertainties":[65],"are":[66,118,121],"taken":[67],"into":[68],"account":[69],"while":[70],"output":[72],"is":[76,88],"interval.":[80],"order":[82,100],"to":[83,101,123],"validate":[84],"it":[87],"implemented":[89],"on":[90,110],"Ontario":[92],"Australian":[94],"markets":[96],"data.":[97],"Also,":[98],"in":[99],"remove":[102],"influence":[104],"parameters":[107],"performance":[111],"validation,":[112],"Friedman":[113],"post-hoc":[115],"tests,":[116,120],"which":[117],"non-parametric":[119],"applied":[122],"method.":[126,139],"The":[127],"results":[128],"demonstrate":[129],"high":[131],"performance,":[132],"accuracy,":[133],"reliability":[135]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":30},{"year":2020,"cited_by_count":40},{"year":2019,"cited_by_count":26},{"year":2018,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
