{"id":"https://openalex.org/W4292264347","doi":"https://doi.org/10.3390/en15165950","title":"Electricity Demand Forecasting with Use of Artificial Intelligence: The Case of Gokceada Island","display_name":"Electricity Demand Forecasting with Use of Artificial Intelligence: The Case of Gokceada Island","publication_year":2022,"publication_date":"2022-08-17","ids":{"openalex":"https://openalex.org/W4292264347","doi":"https://doi.org/10.3390/en15165950"},"language":"en","primary_location":{"id":"doi:10.3390/en15165950","doi":"https://doi.org/10.3390/en15165950","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en15165950","pdf_url":"https://www.mdpi.com/1996-1073/15/16/5950/pdf?version=1660724656","source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Energies","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1996-1073/15/16/5950/pdf?version=1660724656","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005151028","display_name":"Mustafa Saglam","orcid":"https://orcid.org/0000-0003-0529-4944","observed_orcids":["https://orcid.org/0000-0003-0529-4944","https://orcid.org/0000-0002-6760-4349"]},"institutions":[{"id":"https://openalex.org/I1330665745","display_name":"Energy Institute","ror":"https://ror.org/03fgcf430","country_code":"GB","type":"other","lineage":["https://openalex.org/I1330665745"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Mustafa Saglam","raw_affiliation_strings":["Energy Institute, Bartlett School Environment, Energy and Resources, University College London, London WC1E 6BT, UK"],"raw_orcid":"https://orcid.org/0000-0003-0529-4944","affiliations":[{"raw_affiliation_string":"Energy Institute, Bartlett School Environment, Energy and Resources, University College London, London WC1E 6BT, UK","institution_ids":["https://openalex.org/I1330665745","https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022594750","display_name":"Catalina Spataru","orcid":"https://orcid.org/0000-0003-3106-8035","observed_orcids":["https://orcid.org/0000-0003-3106-8035"]},"institutions":[{"id":"https://openalex.org/I1330665745","display_name":"Energy Institute","ror":"https://ror.org/03fgcf430","country_code":"GB","type":"other","lineage":["https://openalex.org/I1330665745"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Catalina Spataru","raw_affiliation_strings":["Energy Institute, Bartlett School Environment, Energy and Resources, University College London, London WC1E 6BT, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Energy Institute, Bartlett School Environment, Energy and Resources, University College London, London WC1E 6BT, UK","institution_ids":["https://openalex.org/I1330665745","https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046235679","display_name":"\u00d6mer Ali Karaman","orcid":"https://orcid.org/0000-0003-1640-861X","observed_orcids":["https://orcid.org/0000-0003-1640-861X"]},"institutions":[{"id":"https://openalex.org/I32481161","display_name":"Batman University","ror":"https://ror.org/051tsqh55","country_code":"TR","type":"education","lineage":["https://openalex.org/I32481161"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Omer Ali Karaman","raw_affiliation_strings":["Department of Electronic and Automation, Vocational School, Batman University, Batman 72100, Turkey"],"raw_orcid":"https://orcid.org/0000-0003-1640-861X","affiliations":[{"raw_affiliation_string":"Department of Electronic and Automation, Vocational School, Batman University, Batman 72100, Turkey","institution_ids":["https://openalex.org/I32481161"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5005151028"],"corresponding_institution_ids":["https://openalex.org/I1330665745","https://openalex.org/I45129253"],"apc_list":{"value":2200,"currency":"CHF","value_usd":2303},"apc_paid":{"value":2200,"currency":"CHF","value_usd":2303},"fwci":2.1799,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.88343805,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"15","issue":"16","first_page":"5950","last_page":"5950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9976000189781189,"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":0.9976000189781189,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/load-forecasting","display_name":"load forecasting","score":1.0},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9279999732971191},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"particle swarm optimization","score":1.0},{"id":"https://openalex.org/keywords/multiple-linear-regression","display_name":"multiple linear regression","score":0.7519999742507935},{"id":"https://openalex.org/keywords/gokceada-island","display_name":"G\u00f6k\u00e7eada Island","score":0.9570000171661377},{"id":"https://openalex.org/keywords/forecast-error-metrics","display_name":"forecast error metrics","score":0.5799999833106995}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7601830959320068},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6875420808792114},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5460247993469238},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5285367369651794},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5281484127044678},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5160093307495117},{"id":"https://openalex.org/C103402496","wikidata":"https://www.wikidata.org/wiki/Q1106171","display_name":"Prediction interval","level":2,"score":0.4863467812538147},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.4830080270767212},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4645756185054779},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.46238771080970764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40649518370628357},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35324954986572266},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3432961702346802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3072429299354553},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2323848307132721},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/en15165950","doi":"https://doi.org/10.3390/en15165950","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en15165950","pdf_url":"https://www.mdpi.com/1996-1073/15/16/5950/pdf?version=1660724656","source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Energies","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:gam:jeners:v:15:y:2022:i:16:p:5950-:d:890153","doi":null,"is_oa":false,"landing_page_url":"https://www.mdpi.com/1996-1073/15/16/5950/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:a55b397351af41deabee80bfef45152a","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/a55b397351af41deabee80bfef45152a","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,"listed_in":[],"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":"Energies, Vol 15, Iss 16, p 5950 (2022)","raw_type":"article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10157081","doi":null,"is_oa":false,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10157081/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Energies , 15 (16) , Article 5950. (2022)","raw_type":"Article"}],"best_oa_location":{"id":"doi:10.3390/en15165950","doi":"https://doi.org/10.3390/en15165950","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en15165950","pdf_url":"https://www.mdpi.com/1996-1073/15/16/5950/pdf?version=1660724656","source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Energies","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.8970999717712402},{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.878000020980835},{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.5351999998092651}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4292264347.pdf","grobid_xml":"https://content.openalex.org/works/W4292264347.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1647404345","https://openalex.org/W2003955416","https://openalex.org/W2092514020","https://openalex.org/W2097137621","https://openalex.org/W2116386142","https://openalex.org/W2165783612","https://openalex.org/W2184527159","https://openalex.org/W2221703650","https://openalex.org/W2621028994","https://openalex.org/W2750292148","https://openalex.org/W2774187023","https://openalex.org/W2890188229","https://openalex.org/W2900243438","https://openalex.org/W2905391149","https://openalex.org/W2911003593","https://openalex.org/W2915043045","https://openalex.org/W2947041956","https://openalex.org/W2970367037","https://openalex.org/W2980869767","https://openalex.org/W2987628917","https://openalex.org/W3001197259","https://openalex.org/W3003839480","https://openalex.org/W3007211815","https://openalex.org/W3011679186","https://openalex.org/W3022211274","https://openalex.org/W3029357900","https://openalex.org/W3046260262","https://openalex.org/W3074782679","https://openalex.org/W3104153263","https://openalex.org/W3135032840","https://openalex.org/W3137201172","https://openalex.org/W3161631405","https://openalex.org/W3162988264","https://openalex.org/W3171592553","https://openalex.org/W3179964283","https://openalex.org/W3183554965","https://openalex.org/W3185376699","https://openalex.org/W3196087597","https://openalex.org/W3197929719","https://openalex.org/W3202517536","https://openalex.org/W3209415817","https://openalex.org/W4213446432","https://openalex.org/W4224280969","https://openalex.org/W4229335382","https://openalex.org/W4282039012","https://openalex.org/W4282560500","https://openalex.org/W4284880617","https://openalex.org/W4292473116"],"related_works":["https://openalex.org/W3173183496","https://openalex.org/W4409803492","https://openalex.org/W2912497388","https://openalex.org/W4236833856","https://openalex.org/W2774187023","https://openalex.org/W6901826883","https://openalex.org/W2510400278","https://openalex.org/W2592418536","https://openalex.org/W2966130868","https://openalex.org/W2590068224"],"abstract_inverted_index":{"This":[0],"study":[1],"reviews":[2],"a":[3],"selection":[4],"of":[5,101,140],"approaches":[6],"that":[7,133],"have":[8,151],"used":[9,42,54,110],"Artificial":[10,30],"Neural":[11,31],"Networks":[12],"(ANN),":[13],"Particle":[14,33],"Swarm":[15,34],"Optimization":[16],"(PSO),":[17],"and":[18,36,50,67,95,119,122,127,146,162],"Multi":[19],"Linear":[20,37],"Regression":[21,38],"(MLR)":[22],"to":[23,62,73,111],"forecast":[24],"electricity":[25,69,159],"demand":[26,160],"for":[27,64,155],"Gokceada":[28,65],"Island.":[29],"Networks,":[32],"Optimization,":[35],"methods":[39,103,157],"are":[40,53,75],"frequently":[41],"in":[43],"the":[44,68,102,113,116,123,136,143,147,152],"literature.":[45],"Imports,":[46],"exports,":[47],"car":[48],"numbers,":[49],"tourist-passenger":[51],"numbers":[52],"as":[55,77,91],"based":[56],"on":[57],"input":[58],"values":[59],"from":[60],"2014":[61],"2020":[63],"Island,":[66],"energy":[70],"demands":[71],"up":[72],"2040":[74],"estimated":[76],"an":[78],"output":[79,161],"value.":[80],"The":[81,97,106],"results":[82],"obtained":[83],"were":[84],"analyzed":[85],"using":[86],"statistical":[87,148],"error":[88,149],"metrics":[89,150],"such":[90],"R2,":[92],"MSE,":[93],"RMSE,":[94],"MAE.":[96],"confidence":[98,138],"interval":[99,139],"analysis":[100],"was":[104,131],"performed.":[105],"correlation":[107,154],"matrix":[108],"is":[109],"show":[112],"relationship":[114,124],"between":[115,125,158],"actual":[117,163],"value":[118],"method":[120,144],"outputs":[121],"independent":[126],"dependent":[128],"variables.":[129],"It":[130],"observed":[132],"ANN":[134,156],"yields":[135],"highest":[137,153],"95%":[141],"among":[142],"utilized,":[145],"data.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":14}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2022-08-19T00:00:00"}
