{"id":"https://openalex.org/W7140231878","doi":"https://doi.org/10.1016/j.procs.2026.03.103","title":"Neural Network-Based Forecasting of Economic Indicators during the COVID-19 Pandemic","display_name":"Neural Network-Based Forecasting of Economic Indicators during the COVID-19 Pandemic","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7140231878","doi":"https://doi.org/10.1016/j.procs.2026.03.103"},"language":"en","primary_location":{"id":"doi:10.1016/j.procs.2026.03.103","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2026.03.103","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.procs.2026.03.103","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bernardo Monteiro","orcid":"https://orcid.org/0009-0000-8048-6116"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bernardo Monteiro","raw_affiliation_strings":["Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal"],"raw_orcid":"https://orcid.org/0009-0000-8048-6116","affiliations":[{"raw_affiliation_string":"Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jos\u00e9 Cavaleiro","orcid":"https://orcid.org/0009-0004-2780-7792"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jos\u00e9 Cavaleiro","raw_affiliation_strings":["Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal"],"raw_orcid":"https://orcid.org/0009-0004-2780-7792","affiliations":[{"raw_affiliation_string":"Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kathleen Carvalho","orcid":"https://orcid.org/0000-0002-8623-7943"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kathleen Carvalho","raw_affiliation_strings":["Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-8623-7943","affiliations":[{"raw_affiliation_string":"Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Jo\u00e3o Paulo Teixeira","orcid":"https://orcid.org/0000-0002-6679-5702"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jo\u00e3o Paulo Teixeira","raw_affiliation_strings":["Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-6679-5702","affiliations":[{"raw_affiliation_string":"Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, 5300-253 Bragan\u00e7a, Portugal","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.63697999,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"278","issue":null,"first_page":"1218","last_page":"1225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.43140000104904175,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.43140000104904175,"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/T11711","display_name":"COVID-19 Pandemic Impacts","score":0.05689999833703041,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.04230000078678131,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/economic-indicator","display_name":"Economic indicator","score":0.6538000106811523},{"id":"https://openalex.org/keywords/gross-domestic-product","display_name":"Gross domestic product","score":0.6295999884605408},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5952000021934509},{"id":"https://openalex.org/keywords/economic-forecasting","display_name":"Economic forecasting","score":0.5856000185012817},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5436999797821045},{"id":"https://openalex.org/keywords/unemployment","display_name":"Unemployment","score":0.5253000259399414},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.47609999775886536},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.42590001225471497},{"id":"https://openalex.org/keywords/economic-impact-analysis","display_name":"Economic impact analysis","score":0.4050999879837036},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.4009000062942505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7601000070571899},{"id":"https://openalex.org/C202353208","wikidata":"https://www.wikidata.org/wiki/Q1167393","display_name":"Economic indicator","level":2,"score":0.6538000106811523},{"id":"https://openalex.org/C114350782","wikidata":"https://www.wikidata.org/wiki/Q12638","display_name":"Gross domestic product","level":2,"score":0.6295999884605408},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5952000021934509},{"id":"https://openalex.org/C163068380","wikidata":"https://www.wikidata.org/wiki/Q3409313","display_name":"Economic forecasting","level":2,"score":0.5856000185012817},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5436999797821045},{"id":"https://openalex.org/C2778126366","wikidata":"https://www.wikidata.org/wiki/Q41171","display_name":"Unemployment","level":2,"score":0.5253000259399414},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4794999957084656},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.47609999775886536},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.42590001225471497},{"id":"https://openalex.org/C188897","wikidata":"https://www.wikidata.org/wiki/Q5333508","display_name":"Economic impact analysis","level":2,"score":0.4050999879837036},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.4009000062942505},{"id":"https://openalex.org/C200941418","wikidata":"https://www.wikidata.org/wiki/Q273508","display_name":"Inflation (cosmology)","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C135510737","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance indicator","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3833000063896179},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37130001187324524},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C119693030","wikidata":"https://www.wikidata.org/wiki/Q2180497","display_name":"Economic model","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.32409998774528503},{"id":"https://openalex.org/C27591710","wikidata":"https://www.wikidata.org/wiki/Q17083572","display_name":"Economic data","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3091999888420105},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C162984825","wikidata":"https://www.wikidata.org/wiki/Q339072","display_name":"Database normalization","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2915000021457672},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C18918823","wikidata":"https://www.wikidata.org/wiki/Q49389","display_name":"Tourism","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.2597000002861023},{"id":"https://openalex.org/C27548731","wikidata":"https://www.wikidata.org/wiki/Q88272","display_name":"Investment (military)","level":3,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.procs.2026.03.103","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2026.03.103","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.procs.2026.03.103","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2026.03.103","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6200478672981262}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334779","display_name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","ror":"https://ror.org/00snfqn58"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2252896288","https://openalex.org/W3034400593","https://openalex.org/W3089749203","https://openalex.org/W3106674355","https://openalex.org/W3112534622","https://openalex.org/W3168712555","https://openalex.org/W4200054040","https://openalex.org/W4205144003","https://openalex.org/W4253629159","https://openalex.org/W4391134020","https://openalex.org/W4394686784","https://openalex.org/W4396591137","https://openalex.org/W4409619897"],"related_works":[],"abstract_inverted_index":{"The":[0,86,137,163,194,241],"COVID-19":[1],"pandemic":[2],"presented":[3],"unprecedented":[4],"challenges":[5],"to":[6,19,41,98,229],"global":[7],"economies,":[8],"revealing":[9],"vulnerabilities":[10],"and":[11,22,55,66,76,83,103,122,144,147,155,181,192,209],"emphasizing":[12],"the":[13,31,160,184,210,244],"urgent":[14],"need":[15],"for":[16,125,190,202,218,252],"predictive":[17,171],"tools":[18,251],"support":[20],"timely":[21],"informed":[23],"decision-making.":[24],"In":[25],"this":[26,28],"context,":[27],"study":[29,242],"investigates":[30],"application":[32],"of":[33,73,216,246],"Multilayer":[34],"Perceptron":[35],"(MLP)":[36],"artificial":[37],"neural":[38],"networks":[39,248],"(ANN)":[40],"forecast":[42],"four":[43],"key":[44],"economic":[45,77,109,235,253],"indicators:":[46],"Gross":[47],"Domestic":[48],"Product":[49],"(GDP),":[50],"unemployment":[51,191],"rate,":[52,54],"inflation":[53],"tourism,":[56],"in":[57,178],"six":[58],"European":[59],"countries":[60],"(Austria,":[61],"France,":[62],"Germany,":[63],"Italy,":[64],"Portugal,":[65],"Spain).":[67],"Based":[68],"on":[69],"a":[70,94,114,129],"time":[71],"series":[72],"public":[74],"health":[75],"data":[78],"collected":[79],"between":[80],"January":[81],"2020":[82],"May":[84],"2023.":[85],"methodology":[87],"involved":[88],"developing":[89],"two":[90],"forecasting":[91,179,231,254],"models:":[92],"(1)":[93],"joint":[95,185,211],"model":[96,186,212],"trained":[97],"predict":[99],"all":[100],"indicators":[101,236],"simultaneously,":[102],"(2)":[104],"independent":[105,174,207],"models,":[106],"where":[107],"each":[108],"indicator":[110],"was":[111,139,200],"forecasted":[112],"using":[113,133,205],"dedicated":[115],"network.":[116],"Data":[117],"preparation":[118],"included":[119],"population-adjusted":[120],"normalization":[121,124],"country-specific":[123],"GDP,":[126],"followed":[127],"by":[128],"sliding":[130],"window":[131],"approach":[132],"30-day":[134],"input":[135],"periods.":[136,257],"dataset":[138],"split":[140],"into":[141],"training,":[142],"validation,":[143],"testing":[145],"subsets,":[146],"experiments":[148],"were":[149],"conducted":[150],"with":[151,173],"varying":[152],"activation":[153],"functions":[154],"hidden":[156],"layer":[157],"configurations":[158],"within":[159],"MLP":[161,247],"networks.":[162],"results":[164,189],"show":[165],"that":[166,223],"both":[167],"approaches":[168],"achieved":[169,213],"high":[170],"accuracy,":[172],"models":[175],"performing":[176],"better":[177],"GDP":[180],"Inflation,":[182],"while":[183],"delivered":[187],"superior":[188],"tourism.":[193],"lowest":[195],"mean":[196],"absolute":[197],"error":[198],"(MAE)":[199],"recorded":[201],"tourism":[203],"(0.0013)":[204],"an":[206,214],"network,":[208],"MAE":[215],"0.0018":[217],"unemployment.":[219],"These":[220],"findings":[221],"highlight":[222],"network":[224],"architecture":[225],"should":[226],"be":[227],"tailored":[228],"specific":[230],"objectives,":[232],"as":[233,249],"different":[234],"benefit":[237],"from":[238],"distinct":[239],"configurations.":[240],"reinforces":[243],"potential":[245],"effective":[250],"during":[255],"crisis":[256]},"counts_by_year":[],"updated_date":"2026-03-25T13:09:30.665167","created_date":"2026-03-25T00:00:00"}