{"id":"https://openalex.org/W4406459561","doi":"https://doi.org/10.1109/bigdata62323.2024.10825486","title":"Development of a Machine Learning Algorithm to Forecast PV Plant Production","display_name":"Development of a Machine Learning Algorithm to Forecast PV Plant Production","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406459561","doi":"https://doi.org/10.1109/bigdata62323.2024.10825486"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5072030444","display_name":"Giovanni Brusco","orcid":"https://orcid.org/0000-0001-9625-2779"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Giovanni Brusco","raw_affiliation_strings":["University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy"],"affiliations":[{"raw_affiliation_string":"University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078135255","display_name":"Daniele Menniti","orcid":null},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Daniele Menniti","raw_affiliation_strings":["University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy"],"affiliations":[{"raw_affiliation_string":"University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115904768","display_name":"Giovanni Schinelli","orcid":null},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giovanni Schinelli","raw_affiliation_strings":["University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy"],"affiliations":[{"raw_affiliation_string":"University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083864019","display_name":"Nicola Sorrentino","orcid":"https://orcid.org/0000-0001-6174-3551"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicola Sorrentino","raw_affiliation_strings":["University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy"],"affiliations":[{"raw_affiliation_string":"University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy","institution_ids":["https://openalex.org/I45204951"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072030444"],"corresponding_institution_ids":["https://openalex.org/I45204951"],"apc_list":null,"apc_paid":null,"fwci":0.222,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57184737,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4673","last_page":"4678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9785000085830688,"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":0.9785000085830688,"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/T14470","display_name":"Advanced Data Processing Techniques","score":0.9387999773025513,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9246000051498413,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.7063230276107788},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6287126541137695},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4215153157711029},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37300044298171997},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36853617429733276}],"concepts":[{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.7063230276107788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6287126541137695},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4215153157711029},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37300044298171997},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36853617429733276},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1901616594","https://openalex.org/W2109628770","https://openalex.org/W2124833832","https://openalex.org/W2146292423","https://openalex.org/W2487770199","https://openalex.org/W2787894218","https://openalex.org/W2911964244","https://openalex.org/W2981018396","https://openalex.org/W4230765542","https://openalex.org/W4232478844","https://openalex.org/W4236362309","https://openalex.org/W4246913152","https://openalex.org/W4251453717","https://openalex.org/W4256141317","https://openalex.org/W4401946675"],"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":{"The":[0,46,61,108],"prediction":[1],"of":[2,13,22,56,68,101,114],"photovoltaic":[3,32,122],"(PV)":[4],"energy":[5,15,33,140],"generation":[6],"is":[7],"crucial":[8],"to":[9,30,52,75,97],"enhance":[10],"the":[11,20,54,65,69,99,102,112],"efficiency":[12],"renewable":[14,139],"systems.":[16],"This":[17],"paper":[18],"proposes":[19],"use":[21,67,129],"machine":[23,71],"learning":[24,72],"models":[25],"such":[26,40],"as":[27,41],"Random":[28,47],"Forest":[29,48],"forecast":[31],"production,":[34],"focusing":[35],"on":[36],"integrating":[37],"environmental":[38],"variables":[39],"temperature,":[42],"humidity,":[43],"wind":[44],"speed.":[45],"model":[49],"was":[50],"implemented":[51],"explore":[53],"influence":[55],"temporal":[57],"and":[58,90,116,138],"meteorological":[59,117],"variables.":[60],"results":[62,109],"indicate":[63],"that":[64],"combined":[66],"advanced":[70],"techniques":[73],"led":[74],"much":[76],"more":[77],"accurate":[78],"forecasts":[79],"measured":[80],"by":[81,105],"Mean":[82,86,91],"Squared":[83],"Error":[84,88,94],"(MSE),":[85],"Absolute":[87,92],"(MAE),":[89],"Percentage":[93],"(MAPE),":[95],"contributing":[96],"improving":[98],"stability":[100],"electrical":[103],"system":[104,123],"reducing":[106],"imbalances.":[107],"obtained":[110],"from":[111,119],"analysis":[113],"historical":[115],"data":[118],"a":[120],"real":[121],"show":[124],"significant":[125],"potential":[126],"for":[127,135],"their":[128],"in":[130],"optimal":[131],"management":[132],"models,":[133],"both":[134],"individual":[136],"users":[137],"communities.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
