{"id":"https://openalex.org/W2987489564","doi":"https://doi.org/10.1080/08839514.2019.1691849","title":"Bankruptcy Prediction Using Stacked Auto-Encoders","display_name":"Bankruptcy Prediction Using Stacked Auto-Encoders","publication_year":2019,"publication_date":"2019-11-14","ids":{"openalex":"https://openalex.org/W2987489564","doi":"https://doi.org/10.1080/08839514.2019.1691849","mag":"2987489564"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2019.1691849","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1691849","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5058981688","display_name":"Makram Soui","orcid":"https://orcid.org/0000-0002-6460-0318"},"institutions":[{"id":"https://openalex.org/I120238654","display_name":"Saudi Electronic University","ror":"https://ror.org/05ndh7v49","country_code":"SA","type":"education","lineage":["https://openalex.org/I120238654"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Makram Soui","raw_affiliation_strings":["College of computing and informatics, Saudi Electronic University, Saudia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of computing and informatics, Saudi Electronic University, Saudia","institution_ids":["https://openalex.org/I120238654"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059057250","display_name":"Salima Smiti","orcid":null},"institutions":[{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Salima Smiti","raw_affiliation_strings":["National School of Computer Science, Manouba, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National School of Computer Science, Manouba, Tunisia","institution_ids":["https://openalex.org/I83259278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067869262","display_name":"Mohamed Wiem Mkaouer","orcid":"https://orcid.org/0000-0001-6010-7561"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed Wiem Mkaouer","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029856197","display_name":"Ridha Ejbali","orcid":"https://orcid.org/0000-0002-8148-1621"},"institutions":[{"id":"https://openalex.org/I68916915","display_name":"University of Gab\u00e8s","ror":"https://ror.org/022efad20","country_code":"TN","type":"education","lineage":["https://openalex.org/I68916915"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Ridha Ejbali","raw_affiliation_strings":["National School of Engineers of Gab\u00e8s, Gab\u00e8s, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National School of Engineers of Gab\u00e8s, Gab\u00e8s, Tunisia","institution_ids":["https://openalex.org/I68916915"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5059057250"],"corresponding_institution_ids":["https://openalex.org/I83259278"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":5.8548,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.95851332,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"34","issue":"1","first_page":"80","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9718000292778015,"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"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9337000250816345,"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/softmax-function","display_name":"Softmax function","score":0.936125636100769},{"id":"https://openalex.org/keywords/bankruptcy-prediction","display_name":"Bankruptcy prediction","score":0.8270466327667236},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7799172401428223},{"id":"https://openalex.org/keywords/bankruptcy","display_name":"Bankruptcy","score":0.7452607750892639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7439118027687073},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6316921710968018},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5576049089431763},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5573955178260803},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5397734045982361},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.523951530456543},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.49757125973701477},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.45225054025650024},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42187929153442383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3328478932380676},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.2402171790599823}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.936125636100769},{"id":"https://openalex.org/C2777388754","wikidata":"https://www.wikidata.org/wiki/Q1664594","display_name":"Bankruptcy prediction","level":3,"score":0.8270466327667236},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7799172401428223},{"id":"https://openalex.org/C504631918","wikidata":"https://www.wikidata.org/wiki/Q152074","display_name":"Bankruptcy","level":2,"score":0.7452607750892639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7439118027687073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6316921710968018},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5576049089431763},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5573955178260803},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5397734045982361},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.523951530456543},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.49757125973701477},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.45225054025650024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42187929153442383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3328478932380676},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2402171790599823},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2019.1691849","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1691849","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2fa224cd6a34470181b11c1eb77ac157","is_oa":false,"landing_page_url":"https://doaj.org/article/2fa224cd6a34470181b11c1eb77ac157","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,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 34, Iss 1, Pp 80-100 (2020)","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W121264339","https://openalex.org/W1175774059","https://openalex.org/W1559740908","https://openalex.org/W1862312035","https://openalex.org/W1967337608","https://openalex.org/W1975102236","https://openalex.org/W1984533548","https://openalex.org/W2005971019","https://openalex.org/W2006680549","https://openalex.org/W2013831240","https://openalex.org/W2015618775","https://openalex.org/W2020848494","https://openalex.org/W2029981389","https://openalex.org/W2048801439","https://openalex.org/W2050731588","https://openalex.org/W2068680128","https://openalex.org/W2070226834","https://openalex.org/W2071193822","https://openalex.org/W2072461903","https://openalex.org/W2076101799","https://openalex.org/W2076278672","https://openalex.org/W2095281267","https://openalex.org/W2117130368","https://openalex.org/W2118023920","https://openalex.org/W2124532504","https://openalex.org/W2128205874","https://openalex.org/W2138027892","https://openalex.org/W2147768505","https://openalex.org/W2158899491","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2184045248","https://openalex.org/W2199996689","https://openalex.org/W2234163201","https://openalex.org/W2253923269","https://openalex.org/W2278229035","https://openalex.org/W2319270064","https://openalex.org/W2502722327","https://openalex.org/W2526016190","https://openalex.org/W2586655365","https://openalex.org/W2590462597","https://openalex.org/W2595840341","https://openalex.org/W2604272474","https://openalex.org/W2606916050","https://openalex.org/W2618249137","https://openalex.org/W2730245908","https://openalex.org/W2766393667","https://openalex.org/W2769949979","https://openalex.org/W2774099057","https://openalex.org/W2783176580","https://openalex.org/W2785729516","https://openalex.org/W2788025656","https://openalex.org/W2789320008","https://openalex.org/W2949888546","https://openalex.org/W2950344723","https://openalex.org/W2951622387","https://openalex.org/W2964046661","https://openalex.org/W3101287485","https://openalex.org/W3214794361","https://openalex.org/W4245076768","https://openalex.org/W4256478528"],"related_works":["https://openalex.org/W2769441402","https://openalex.org/W2594436708","https://openalex.org/W4360994128","https://openalex.org/W3086240734","https://openalex.org/W2736305774","https://openalex.org/W2951850672","https://openalex.org/W2285942202","https://openalex.org/W4237436108","https://openalex.org/W2241582670","https://openalex.org/W2347342407"],"abstract_inverted_index":{"Bankruptcy":[0],"prediction":[1],"is":[2,19,134],"considered":[3],"as":[4,49],"one":[5,94],"of":[6,16,73,99,149,160],"the":[7,33,112,115,122,126,138,147,158,161],"vital":[8],"topics":[9],"in":[10],"finance":[11],"and":[12,55,90,151],"accounting.":[13],"The":[14,154],"purpose":[15],"predicting":[17,97],"bankruptcy":[18,98],"to":[20,62,120,136,167,171],"build":[21],"a":[22,71,80,130],"predictive":[23],"model":[24,95],"that":[25],"combines":[26,104],"several":[27],"econometrics":[28],"parameters,":[29],"which":[30,85],"allow":[31],"evaluating":[32],"firm":[34],"financial":[35,100],"status":[36],"either":[37],"bankrupt":[38],"or":[39],"non-bankrupt.":[40],"In":[41,111],"this":[42,76],"field,":[43],"various":[44],"machine":[45],"learning":[46,67],"algorithms":[47,68],"such":[48],"decision":[50],"tree,":[51],"support":[52],"vector":[53],"machine,":[54],"artificial":[56],"neural":[57],"network":[58],"have":[59],"been":[60],"applied":[61],"predict":[63,137,173],"bankruptcy.":[64,175],"However,":[65],"deep":[66,82],"are":[69,118],"experiencing":[70],"resurgence":[72],"interest.":[74],"To":[75],"end,":[77],"we":[78],"propose":[79],"novel":[81],"learning-based":[83],"approach":[84,103,145],"includes":[86],"both":[87],"feature":[88],"extraction":[89],"classification":[91,132],"phase":[92],"into":[93],"for":[96],"firms.":[101],"Our":[102],"Stacked":[105],"Auto-Encoders":[106],"(SAE)":[107],"with":[108,163],"softmax":[109,131,164],"classifier.":[110],"first":[113],"stage,":[114],"stacked":[116],"auto-encoders":[117],"employed":[119],"extract":[121],"best":[123],"features":[124],"from":[125],"training":[127],"dataset.":[128],"Second,":[129],"layer":[133],"trained":[135],"class":[139],"label.":[140],"We":[141],"evaluate":[142],"our":[143],"proposed":[144],"on":[146],"base":[148],"Polish":[150],"Darden":[152],"datasets.":[153],"obtained":[155],"results":[156],"confirm":[157],"efficiency":[159],"SAE":[162],"classifier":[165],"compared":[166],"other":[168],"existing":[169],"works":[170],"accurately":[172],"corporate":[174]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}