{"id":"https://openalex.org/W7162829342","doi":null,"title":"Electricity Demand Forecasting at the Duques de Soria Campus Using Machine Learning Techniques","display_name":"Electricity Demand Forecasting at the Duques de Soria Campus Using Machine Learning Techniques","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7162829342"},"language":"en","primary_location":{"id":"pmh:oai:uvadoc.uva.es:10324/84820","doi":null,"is_oa":true,"landing_page_url":"https://uvadoc.uva.es/handle/10324/84820","pdf_url":"https://uvadoc.uva.es/bitstream/10324/84820/1/TFM-O-96.pdf","source":{"id":"https://openalex.org/S4306400688","display_name":"University of Valladolid Documentary Repository (University of Valladolid)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I108103353","host_organization_name":"Universidad de Valladolid","host_organization_lineage":["https://openalex.org/I108103353"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/masterThesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://uvadoc.uva.es/bitstream/10324/84820/1/TFM-O-96.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123415191","display_name":"Ghada Amami","orcid":"https://orcid.org/0009-0009-3422-185X","observed_orcids":["https://orcid.org/0009-0009-3422-185X"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Amami, Ghada","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5123415191"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9984999895095825,"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":0.9984999895095825,"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/T10603","display_name":"Smart Grid Energy Management","score":0.000699999975040555,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/load-forecasting","display_name":"load forecasting","score":0.8650000095367432},{"id":"https://openalex.org/keywords/short-term-load-forecasting","display_name":"short-term load forecasting","score":0.9660000205039978},{"id":"https://openalex.org/keywords/smart-meter-data","display_name":"smart meter data","score":0.8389999866485596},{"id":"https://openalex.org/keywords/university-campus-energy-consumption","display_name":"university campus energy consumption","score":0.828000009059906},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.843999981880188},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":0.9629999995231628},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.7329999804496765},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"feature engineering","score":0.6460000276565552},{"id":"https://openalex.org/keywords/temporal-characteristics","display_name":"temporal features","score":0.6919999718666077},{"id":"https://openalex.org/keywords/weather-effects-on-load","display_name":"weather effects on load","score":0.7480000257492065},{"id":"https://openalex.org/keywords/sustainable-energy-management","display_name":"sustainable energy management","score":0.8790000081062317}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.66839998960495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6021000146865845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5906000137329102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5856000185012817},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5544000267982483},{"id":"https://openalex.org/C2779510800","wikidata":"https://www.wikidata.org/wiki/Q1630602","display_name":"Smart meter","level":3,"score":0.4927000105381012},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.4821999967098236},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.45989999175071716},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4505000114440918},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.41620001196861267},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.38749998807907104},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.33880001306533813},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.30970001220703125},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.29809999465942383},{"id":"https://openalex.org/C2988649059","wikidata":"https://www.wikidata.org/wiki/Q1853339","display_name":"Electricity demand","level":4,"score":0.29750001430511475},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.29670000076293945},{"id":"https://openalex.org/C2779438525","wikidata":"https://www.wikidata.org/wiki/Q5255048","display_name":"Demand response","level":3,"score":0.2896000146865845},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28060001134872437},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C2987469573","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather prediction","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:uvadoc.uva.es:10324/84820","doi":null,"is_oa":true,"landing_page_url":"https://uvadoc.uva.es/handle/10324/84820","pdf_url":"https://uvadoc.uva.es/bitstream/10324/84820/1/TFM-O-96.pdf","source":{"id":"https://openalex.org/S4306400688","display_name":"University of Valladolid Documentary Repository (University of Valladolid)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I108103353","host_organization_name":"Universidad de Valladolid","host_organization_lineage":["https://openalex.org/I108103353"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/masterThesis"}],"best_oa_location":{"id":"pmh:oai:uvadoc.uva.es:10324/84820","doi":null,"is_oa":true,"landing_page_url":"https://uvadoc.uva.es/handle/10324/84820","pdf_url":"https://uvadoc.uva.es/bitstream/10324/84820/1/TFM-O-96.pdf","source":{"id":"https://openalex.org/S4306400688","display_name":"University of Valladolid Documentary Repository (University of Valladolid)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I108103353","host_organization_name":"Universidad de Valladolid","host_organization_lineage":["https://openalex.org/I108103353"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/masterThesis"},"sustainable_development_goals":[{"score":0.5690000057220459,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"},{"score":0.5351999998092651,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7162829342.pdf","grobid_xml":"https://content.openalex.org/works/W7162829342.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2144335970","https://openalex.org/W2804385782","https://openalex.org/W2945137668","https://openalex.org/W2980876613","https://openalex.org/W3006150655","https://openalex.org/W3022643593","https://openalex.org/W3041303727","https://openalex.org/W3044436817","https://openalex.org/W3109306670","https://openalex.org/W3114612967","https://openalex.org/W3122220845","https://openalex.org/W3128290931","https://openalex.org/W3198618412","https://openalex.org/W3204201639","https://openalex.org/W3208096233","https://openalex.org/W4213021104","https://openalex.org/W4280539053","https://openalex.org/W4281936363","https://openalex.org/W4294287031","https://openalex.org/W4310154744","https://openalex.org/W4318141878","https://openalex.org/W4362735283","https://openalex.org/W4378907691","https://openalex.org/W4385455859","https://openalex.org/W4386420419","https://openalex.org/W4386453649","https://openalex.org/W4388020818","https://openalex.org/W4388551144","https://openalex.org/W4389261544","https://openalex.org/W4389268416","https://openalex.org/W4389350202","https://openalex.org/W4389512180","https://openalex.org/W4393356874","https://openalex.org/W4394923553","https://openalex.org/W4396850220","https://openalex.org/W4396863907","https://openalex.org/W4399327652","https://openalex.org/W4400268954","https://openalex.org/W4401891568","https://openalex.org/W4405031072"],"related_works":["https://openalex.org/W7124836137","https://openalex.org/W7172332977","https://openalex.org/W7110633050","https://openalex.org/W7223170686","https://openalex.org/W7133440984","https://openalex.org/W7161280285","https://openalex.org/W7127252123","https://openalex.org/W4408548378","https://openalex.org/W7116839962","https://openalex.org/W7142685744"],"abstract_inverted_index":{"This":[0,151],"master's":[1],"thesis":[2],"presents":[3],"a":[4],"short-term":[5],"electricity":[6],"demand":[7],"forecasting":[8,165],"model":[9,72],"for":[10],"the":[11,45,48,74,86,109,143,147],"Duques":[12],"de":[13],"Soria":[14],"campus":[15],"in":[16],"Spain,":[17],"using":[18],"machine":[19],"learning":[20],"techniques":[21],"including":[22],"Random":[23],"Forest":[24],"(RF),":[25],"Multi-Layer":[26],"Perceptron":[27],"(MLP),":[28],"and":[29,60,71,82,94,117,138],"Long":[30],"Short-Term":[31],"Memory":[32],"(LSTM)":[33],"networks.":[34],"Based":[35],"on":[36,157],"six":[37],"years":[38],"of":[39,50,92,97],"hourly":[40,144],"smart":[41],"meter":[42],"data":[43,67,120],"(2019\u20132024),":[44],"study":[46,125],"explores":[47],"impact":[49],"various":[51],"features\u2014such":[52],"as":[53,133,135],"lagged":[54],"load,":[55],"temporal":[56,140],"variables,":[57],"calendar":[58],"indicators,":[59],"weather":[61],"conditions\u2014on":[62],"prediction":[63],"performance.":[64],"After":[65],"thorough":[66],"cleaning,":[68],"feature":[69,129],"engineering,":[70],"optimization,":[73],"RF":[75],"model,":[76],"which":[77],"utilized":[78],"only":[79],"historical":[80],"load":[81],"hour":[83],"features,":[84],"achieved":[85],"best":[87],"results":[88],"with":[89,105,108],"an":[90,95],"MAPE":[91,107],"9.51%":[93],"MAE":[96],"5.95.":[98],"While":[99],"MLP":[100],"showed":[101],"strong":[102],"robustness":[103],"result":[104],"9.66%":[106],"same":[110],"senario,":[111],"Though":[112],"LSTM":[113],"required":[114],"richer":[115],"sequences":[116],"more":[118,162],"training":[119],"to":[121],"perform":[122],"better.":[123],"The":[124],"concludes":[126],"that":[127,139],"careful":[128],"selection":[130],"is":[131],"just":[132],"crucial":[134],"algorithm":[136],"choice,":[137],"features":[141],"at":[142],"scale":[145],"provide":[146],"highest":[148],"predictive":[149],"power.":[150],"work":[152],"supports":[153],"sustainable":[154],"energy":[155],"management":[156],"university":[158],"campuses":[159],"by":[160],"enabling":[161],"accurate,":[163],"data-driven":[164]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-05-30T00:00:00"}
