{"id":"https://openalex.org/W4416978076","doi":"https://doi.org/10.1186/s40537-025-01318-z","title":"Artificial intelligence and classical statistical models for time series forecasting: a comprehensive review","display_name":"Artificial intelligence and classical statistical models for time series forecasting: a comprehensive review","publication_year":2025,"publication_date":"2025-12-04","ids":{"openalex":"https://openalex.org/W4416978076","doi":"https://doi.org/10.1186/s40537-025-01318-z"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-025-01318-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01318-z","pdf_url":null,"source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s40537-025-01318-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056436780","display_name":"Essam H. Houssein","orcid":"https://orcid.org/0000-0002-8127-7233"},"institutions":[{"id":"https://openalex.org/I89466785","display_name":"Minia University","ror":"https://ror.org/02hcv4z63","country_code":"EG","type":"education","lineage":["https://openalex.org/I89466785"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Essam H. Houssein","raw_affiliation_strings":["Faculty of Computers and Information, Minia University, Minia, Egypt","Minia National University, Minia, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computers and Information, Minia University, Minia, Egypt","institution_ids":["https://openalex.org/I89466785"]},{"raw_affiliation_string":"Minia National University, Minia, Egypt","institution_ids":["https://openalex.org/I89466785"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Meran Mohamed","orcid":null},"institutions":[{"id":"https://openalex.org/I89466785","display_name":"Minia University","ror":"https://ror.org/02hcv4z63","country_code":"EG","type":"education","lineage":["https://openalex.org/I89466785"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Meran Mohamed","raw_affiliation_strings":["Faculty of Computers and Information, Minia University, Minia, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computers and Information, Minia University, Minia, Egypt","institution_ids":["https://openalex.org/I89466785"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069389579","display_name":"Eman M. G. Younis","orcid":"https://orcid.org/0000-0003-2778-4231"},"institutions":[{"id":"https://openalex.org/I89466785","display_name":"Minia University","ror":"https://ror.org/02hcv4z63","country_code":"EG","type":"education","lineage":["https://openalex.org/I89466785"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Eman M. G. Younis","raw_affiliation_strings":["Faculty of Computers and Information, Minia University, Minia, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computers and Information, Minia University, Minia, Egypt","institution_ids":["https://openalex.org/I89466785"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086295431","display_name":"Waleed M. Mohamed","orcid":"https://orcid.org/0000-0002-2516-5800"},"institutions":[{"id":"https://openalex.org/I89466785","display_name":"Minia University","ror":"https://ror.org/02hcv4z63","country_code":"EG","type":"education","lineage":["https://openalex.org/I89466785"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Waleed M. Mohamed","raw_affiliation_strings":["Faculty of Computers and Information, Minia University, Minia, Egypt","Minia National University, Minia, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computers and Information, Minia University, Minia, Egypt","institution_ids":["https://openalex.org/I89466785"]},{"raw_affiliation_string":"Minia National University, Minia, Egypt","institution_ids":["https://openalex.org/I89466785"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056436780"],"corresponding_institution_ids":["https://openalex.org/I89466785"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":3.6921,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.94176116,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"12","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.46790000796318054,"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":0.46790000796318054,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.08330000191926956,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.05770000070333481,"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/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.5863000154495239},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5590999722480774},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4683000147342682},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.46619999408721924},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4535999894142151},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.41179999709129333},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3702999949455261},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.3538999855518341}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8136000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7092999815940857},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6119999885559082},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.5863000154495239},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5590999722480774},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4683000147342682},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4535999894142151},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3702999949455261},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C161657586","wikidata":"https://www.wikidata.org/wiki/Q1203326","display_name":"Technology forecasting","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2759999930858612},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-025-01318-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01318-z","pdf_url":null,"source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b879e4cb59d8454b8727c823dc38116e","is_oa":true,"landing_page_url":"https://doaj.org/article/b879e4cb59d8454b8727c823dc38116e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 12, Iss 1, Pp 1-38 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-025-01318-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01318-z","pdf_url":null,"source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320327648","display_name":"Minia University","ror":"https://ror.org/02hcv4z63"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":144,"referenced_works":["https://openalex.org/W883434633","https://openalex.org/W1498436455","https://openalex.org/W1595159159","https://openalex.org/W1678356000","https://openalex.org/W1967690950","https://openalex.org/W1975009952","https://openalex.org/W1995341919","https://openalex.org/W2001422417","https://openalex.org/W2014928429","https://openalex.org/W2031183907","https://openalex.org/W2055877700","https://openalex.org/W2064675550","https://openalex.org/W2069508080","https://openalex.org/W2072955302","https://openalex.org/W2077179900","https://openalex.org/W2110603299","https://openalex.org/W2131453387","https://openalex.org/W2132782512","https://openalex.org/W2178225550","https://openalex.org/W2180110293","https://openalex.org/W2187731079","https://openalex.org/W2301106258","https://openalex.org/W2306115793","https://openalex.org/W2484997644","https://openalex.org/W2523498403","https://openalex.org/W2552338890","https://openalex.org/W2607162077","https://openalex.org/W2609559763","https://openalex.org/W2657631929","https://openalex.org/W2728943311","https://openalex.org/W2777051231","https://openalex.org/W2789399411","https://openalex.org/W2798629644","https://openalex.org/W2799656149","https://openalex.org/W2801889078","https://openalex.org/W2806777472","https://openalex.org/W2865675487","https://openalex.org/W2893738649","https://openalex.org/W2900453322","https://openalex.org/W2901374262","https://openalex.org/W2905967367","https://openalex.org/W2907856150","https://openalex.org/W2911964244","https://openalex.org/W2912036663","https://openalex.org/W2914487400","https://openalex.org/W2916525543","https://openalex.org/W2919979744","https://openalex.org/W2922059200","https://openalex.org/W2938308298","https://openalex.org/W2940914091","https://openalex.org/W2944185501","https://openalex.org/W2944481087","https://openalex.org/W2946030813","https://openalex.org/W2963103847","https://openalex.org/W2986266941","https://openalex.org/W2995296280","https://openalex.org/W2995317627","https://openalex.org/W2997857369","https://openalex.org/W3008871396","https://openalex.org/W3012629428","https://openalex.org/W3014974411","https://openalex.org/W3016445506","https://openalex.org/W3016784573","https://openalex.org/W3017116930","https://openalex.org/W3018758730","https://openalex.org/W3021785726","https://openalex.org/W3030898280","https://openalex.org/W3033154016","https://openalex.org/W3042316884","https://openalex.org/W3043008751","https://openalex.org/W3044909247","https://openalex.org/W3047937490","https://openalex.org/W3080253043","https://openalex.org/W3082523044","https://openalex.org/W3088775243","https://openalex.org/W3094497334","https://openalex.org/W3107642158","https://openalex.org/W3155398915","https://openalex.org/W3164362328","https://openalex.org/W3171884590","https://openalex.org/W3173891635","https://openalex.org/W3175286348","https://openalex.org/W3176196442","https://openalex.org/W3177318507","https://openalex.org/W3178134178","https://openalex.org/W3188779816","https://openalex.org/W3196681873","https://openalex.org/W3198316914","https://openalex.org/W3199148273","https://openalex.org/W3212711508","https://openalex.org/W3213652448","https://openalex.org/W3216578860","https://openalex.org/W4200576739","https://openalex.org/W4205761263","https://openalex.org/W4206455715","https://openalex.org/W4210580908","https://openalex.org/W4220876020","https://openalex.org/W4246598646","https://openalex.org/W4281691680","https://openalex.org/W4283067767","https://openalex.org/W4286215040","https://openalex.org/W4287218463","https://openalex.org/W4306953826","https://openalex.org/W4307269040","https://openalex.org/W4307727243","https://openalex.org/W4308417351","https://openalex.org/W4309903464","https://openalex.org/W4312864314","https://openalex.org/W4314446242","https://openalex.org/W4319293925","https://openalex.org/W4321782037","https://openalex.org/W4322102495","https://openalex.org/W4322724021","https://openalex.org/W4365450435","https://openalex.org/W4381186711","https://openalex.org/W4385066516","https://openalex.org/W4385377104","https://openalex.org/W4385948404","https://openalex.org/W4386160141","https://openalex.org/W4386189827","https://openalex.org/W4387319325","https://openalex.org/W4387706023","https://openalex.org/W4388751946","https://openalex.org/W4391074157","https://openalex.org/W4392453192","https://openalex.org/W4392453423","https://openalex.org/W4394804419","https://openalex.org/W4400033304","https://openalex.org/W4400111388","https://openalex.org/W4401353384","https://openalex.org/W4402023304","https://openalex.org/W4402678208","https://openalex.org/W4403123254","https://openalex.org/W4403420425","https://openalex.org/W4404339145","https://openalex.org/W4404635490","https://openalex.org/W4404725237","https://openalex.org/W4405316779","https://openalex.org/W4406056991","https://openalex.org/W4406490152","https://openalex.org/W4407556541","https://openalex.org/W4408338798","https://openalex.org/W4408842725","https://openalex.org/W4410614598"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Time":[1],"series":[2,170],"forecasting":[3,51,93,171],"plays":[4],"a":[5,160],"critical":[6],"role":[7],"in":[8,108],"decision-making":[9],"across":[10],"diverse":[11],"domains":[12],"such":[13],"as":[14,159],"finance,":[15],"healthcare,":[16],"and":[17,28,36,47,53,70,89,111,122,139,149,174],"environmental":[18,123],"monitoring.":[19],"While":[20],"classical":[21],"statistical":[22],"models":[23,104,132],"like":[24],"ARIMA":[25],"remain":[26],"interpretable":[27],"efficient,":[29],"they":[30],"often":[31],"struggle":[32],"with":[33,87],"nonlinear":[34],"patterns":[35],"dynamic":[37],"dependencies.":[38],"This":[39,156],"review":[40],"systematically":[41],"examines":[42],"how":[43],"artificial":[44],"intelligence":[45],"(AI)":[46],"optimization":[48,175],"techniques":[49],"enhance":[50],"accuracy":[52,94],"robustness.":[54],"We":[55],"evaluate":[56],"modern":[57],"deep":[58,81],"learning":[59],"architectures":[60,151],"(e.g.,":[61,67],"LSTM,":[62],"GRU,":[63],"Transformers),":[64],"hybrid":[65],"frameworks":[66],"VMD-LSTM,":[68],"CNN-GRU),":[69],"optimization-augmented":[71],"models.":[72],"A":[73],"meta-analysis":[74],"of":[75,168],"over":[76],"150":[77],"studies":[78],"reveals":[79],"that":[80],"learning-based":[82],"approaches,":[83],"particularly":[84],"those":[85],"enhanced":[86],"Adam":[88],"RMSProp":[90],"optimizers,":[91],"improve":[92],"by":[95],"up":[96],"to":[97,100,152],"14%":[98],"compared":[99],"traditional":[101],"methods.":[102],"Hybrid":[103],"demonstrate":[105],"superior":[106],"performance":[107],"multi-step":[109],"predictions":[110],"handling":[112],"volatility.":[113],"The":[114],"analysis":[115],"includes":[116],"financial":[117],"datasets":[118],"(S&P":[119],"500,":[120],"NASDAQ)":[121],"data":[124,140],"(Beijing":[125],"$$PM_{2.5}$$":[126],").":[127],"Despite":[128],"their":[129],"power,":[130],"AI-driven":[131],"face":[133],"challenges":[134],"including":[135],"interpretability,":[136],"computational":[137],"cost,":[138],"dependency.":[141],"Future":[142],"directions":[143],"highlight":[144],"explainable":[145],"AI,":[146],"transfer":[147],"learning,":[148],"lightweight":[150],"address":[153],"these":[154],"limitations.":[155],"work":[157],"serves":[158],"reference":[161],"for":[162],"researchers":[163],"exploring":[164],"the":[165],"evolving":[166],"landscape":[167],"time":[169],"through":[172],"AI":[173],"integration.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-05-02T08:42:23.175194","created_date":"2025-12-04T00:00:00"}