{"id":"https://openalex.org/W4407304356","doi":"https://doi.org/10.1109/access.2025.3540636","title":"The Effect of Input Length on Prediction Accuracy in Short-Term Multi-Step Electricity Load Forecasting: A CNN-LSTM Approach","display_name":"The Effect of Input Length on Prediction Accuracy in Short-Term Multi-Step Electricity Load Forecasting: A CNN-LSTM Approach","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407304356","doi":"https://doi.org/10.1109/access.2025.3540636"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3540636","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3540636","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3540636","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116209752","display_name":"\u015eeyda \u00d6zdemir","orcid":"https://orcid.org/0009-0001-2866-1391"},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"\u015eeyda \u00d6zdem\u0131r","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, I&#x011F;d&#x0131;r University, I&#x011F;&#x0131;rat, T&#x00FC;rkiye","Department of Electrical and Electronics Engineering, I&#x011F;d&#x0131;r University, I&#x011F;d&#x0131;r, TR, Turkey"],"raw_orcid":"https://orcid.org/0009-0001-2866-1391","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, I&#x011F;d&#x0131;r University, I&#x011F;&#x0131;rat, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]},{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, I&#x011F;d&#x0131;r University, I&#x011F;d&#x0131;r, TR, Turkey","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102706549","display_name":"Yakup Demir","orcid":"https://orcid.org/0000-0001-9530-5824"},"institutions":[{"id":"https://openalex.org/I143396566","display_name":"F\u0131rat University","ror":"https://ror.org/05teb7b63","country_code":"TR","type":"education","lineage":["https://openalex.org/I143396566"]},{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE","TR"],"is_corresponding":false,"raw_author_name":"Yakup Dem\u0131r","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, F&#x0131;rat University, Elaz&#x0131;&#x011F;, T&#x00FC;rkiye","Department of Electrical and Electronics Engineering, Firat University, Elaz&#x0131;&#x011F;, TR, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, F&#x0131;rat University, Elaz&#x0131;&#x011F;, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]},{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Firat University, Elaz&#x0131;&#x011F;, TR, Turkey","institution_ids":["https://openalex.org/I143396566"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083618632","display_name":"\u00d6zal Y\u0131ld\u0131r\u0131m","orcid":"https://orcid.org/0000-0001-5375-3012"},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"\u00d6zal Yildirim","raw_affiliation_strings":["Faculty of Technology, F&#x0131;rat University, Elaz&#x0131;&#x011F;, T&#x00FC;rkiye","Faculty of Technology, F&#x0131;rat University, Elaz&#x0131;&#x011F;, TR, Turkey"],"raw_orcid":"https://orcid.org/0000-0001-5375-3012","affiliations":[{"raw_affiliation_string":"Faculty of Technology, F&#x0131;rat University, Elaz&#x0131;&#x011F;, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]},{"raw_affiliation_string":"Faculty of Technology, F&#x0131;rat University, Elaz&#x0131;&#x011F;, TR, Turkey","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5116209752"],"corresponding_institution_ids":["https://openalex.org/I2799978770"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":7.5028,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.9723389,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"28419","last_page":"28432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9936000108718872,"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":0.9936000108718872,"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/T14276","display_name":"Power Systems and Technologies","score":0.9699000120162964,"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/T12451","display_name":"Smart Grid and Power Systems","score":0.9476000070571899,"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/term","display_name":"Term (time)","score":0.8252904415130615},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7382366061210632},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.4921039938926697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47758057713508606},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3846518397331238},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06609269976615906}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.8252904415130615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7382366061210632},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.4921039938926697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47758057713508606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3846518397331238},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06609269976615906},{"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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3540636","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3540636","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:17ab2e53330f46508dcf3968205f4005","is_oa":true,"landing_page_url":"https://doaj.org/article/17ab2e53330f46508dcf3968205f4005","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 28419-28432 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3540636","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3540636","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2123007178","https://openalex.org/W2490223215","https://openalex.org/W2597866042","https://openalex.org/W2754252319","https://openalex.org/W2948490758","https://openalex.org/W2964951176","https://openalex.org/W2984347565","https://openalex.org/W3008314711","https://openalex.org/W3043685378","https://openalex.org/W3046976979","https://openalex.org/W3048216458","https://openalex.org/W3084535629","https://openalex.org/W3090661556","https://openalex.org/W3095469347","https://openalex.org/W3125531171","https://openalex.org/W3128617977","https://openalex.org/W3129762955","https://openalex.org/W3130388336","https://openalex.org/W3131110071","https://openalex.org/W3133147635","https://openalex.org/W3137224754","https://openalex.org/W3142394151","https://openalex.org/W3163598860","https://openalex.org/W3197015000","https://openalex.org/W3200680133","https://openalex.org/W3201109720","https://openalex.org/W3207985790","https://openalex.org/W3208556378","https://openalex.org/W4205163407","https://openalex.org/W4205809857","https://openalex.org/W4220832572","https://openalex.org/W4280574751","https://openalex.org/W4283158759","https://openalex.org/W4293799812","https://openalex.org/W4365790152","https://openalex.org/W4386858444","https://openalex.org/W4387729966","https://openalex.org/W4400033614"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Accurate":[0],"load":[1,37,70],"forecasting":[2,38,71,158,170],"is":[3,32,82,164],"crucial":[4],"for":[5,43,67,111],"effective":[6],"power":[7],"system":[8,44],"management":[9],"and":[10,26,61,143],"planning":[11],"in":[12,137,145],"the":[13,21,101,105,109,122,156,168],"context":[14],"of":[15,23,108,135],"growing":[16],"electricity":[17],"demand":[18],"triggered":[19],"by":[20],"proliferation":[22],"technological":[24],"devices":[25],"rapid":[27],"digitalization.":[28],"Since":[29],"electrical":[30,36],"energy":[31],"largely":[33],"non-storable,":[34],"short-term":[35,63,68],"plays":[39],"a":[40,77],"critical":[41],"role":[42],"operators.":[45],"This":[46],"paper":[47],"presents":[48],"an":[49,117,133],"innovative":[50],"hybrid":[51],"deep":[52],"learning":[53,106],"model":[54,81,110],"that":[55,99,155],"combines":[56],"convolutional":[57],"neural":[58],"networks":[59,66],"(CNNs)":[60],"long":[62],"memory":[64],"(LSTM)":[65],"multi-step":[69,157],"using":[72],"real-time":[73],"hourly":[74],"data":[75],"from":[76],"residential":[78],"customer.":[79],"The":[80,96],"tested":[83],"on":[84],"12":[85],"different":[86],"configurations":[87],"with":[88,132,160],"symmetrically":[89],"increasing":[90,100],"input":[91,102,118,162],"lengths,":[92],"including":[93],"weather":[94],"data.":[95],"results":[97],"show":[98],"length":[103,119,124,163],"improves":[104],"performance":[107,159],"all":[112],"conditions.":[113],"In":[114],"addition,":[115],"selecting":[116],"greater":[120],"than":[121,167],"output":[123],"has":[125],"been":[126],"shown":[127],"to":[128],"improve":[129],"prediction":[130],"accuracy,":[131],"improvement":[134],"67%":[136],"Mean":[138,147],"Absolute":[139],"Percentage":[140],"Error":[141,149],"(MAPE)":[142],"70%":[144],"Root":[146],"Square":[148],"(RMSE).":[150],"Moreover,":[151],"it":[152],"was":[153],"observed":[154],"increased":[161],"more":[165],"successful":[166],"single-step":[169],"performance.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
