{"id":"https://openalex.org/W2138476575","doi":"https://doi.org/10.1109/icmlc.2002.1175325","title":"Neural network credit-risk evaluation model based on back-propagation algorithm","display_name":"Neural network credit-risk evaluation model based on back-propagation algorithm","publication_year":2003,"publication_date":"2003-06-26","ids":{"openalex":"https://openalex.org/W2138476575","doi":"https://doi.org/10.1109/icmlc.2002.1175325","mag":"2138476575"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2002.1175325","doi":"https://doi.org/10.1109/icmlc.2002.1175325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2002.1175325","pdf_url":null,"source":{"id":"https://openalex.org/S4306419646","display_name":"International Conference on Machine Learning and Cybernetics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5009373931","display_name":"Rongzhou Li","orcid":"https://orcid.org/0009-0000-4543-2673","observed_orcids":["https://orcid.org/0009-0000-4543-2673"]},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong-Zhou Li","raw_affiliation_strings":["College of Traffic and Communications, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Traffic and Communications, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653120","display_name":"Sulin Pang","orcid":"https://orcid.org/0000-0001-7190-2472","observed_orcids":["https://orcid.org/0000-0001-7190-2472","https://orcid.org/0000-0002-6395-8166"]},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Su-Lin Pang","raw_affiliation_strings":["Department of Mathematics, Jinan University, Guangzhou, China","School of Mathematics & Lingnan College, Zhongshan University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]},{"raw_affiliation_string":"School of Mathematics & Lingnan College, Zhongshan University, Guangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101974137","display_name":"Jianmin Xu","orcid":"https://orcid.org/0000-0002-8922-8815","observed_orcids":["https://orcid.org/0000-0002-8922-8815"]},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian-Min Xu","raw_affiliation_strings":["Department of Mathematics, Jinan University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.26680672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"4","issue":null,"first_page":"1702","last_page":"1706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9541000127792358,"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":0.9541000127792358,"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/T14368","display_name":"Evaluation and Optimization Models","score":0.027699999511241913,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10320","display_name":"Neural Networks and Applications","score":0.0071000000461936,"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/credit-risk-assessment","display_name":"credit risk assessment","score":0.8939999938011169},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.7149999737739563},{"id":"https://openalex.org/keywords/back-propagation-algorithm","display_name":"back-propagation algorithm","score":0.9599999785423279},{"id":"https://openalex.org/keywords/credit-scoring","display_name":"credit scoring","score":0.6079999804496765},{"id":"https://openalex.org/keywords/linear-discriminant-analysis-comparison","display_name":"linear discriminant analysis comparison","score":0.9279999732971191},{"id":"https://openalex.org/keywords/credit-risk-classification","display_name":"credit risk classification","score":0.3479999899864197}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7664222121238708},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.7185739874839783},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.6811282634735107},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.667424201965332},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6250479221343994},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5394599437713623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5308884978294373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48821118474006653},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.356588214635849},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2323472499847412},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.1120404303073883}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2002.1175325","doi":"https://doi.org/10.1109/icmlc.2002.1175325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2002.1175325","pdf_url":null,"source":{"id":"https://openalex.org/S4306419646","display_name":"International Conference on Machine Learning and Cybernetics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1964074981","https://openalex.org/W1976026757","https://openalex.org/W1992853911","https://openalex.org/W2014647052","https://openalex.org/W2016207894","https://openalex.org/W2025294397","https://openalex.org/W2036753645","https://openalex.org/W2064031858","https://openalex.org/W2081663933","https://openalex.org/W2093829413"],"related_works":["https://openalex.org/W2354757274","https://openalex.org/W4249697958","https://openalex.org/W2038313399","https://openalex.org/W1990113270","https://openalex.org/W2366048417","https://openalex.org/W2035279783","https://openalex.org/W2303097976","https://openalex.org/W4233971095","https://openalex.org/W2941240394","https://openalex.org/W2157273561"],"abstract_inverted_index":{"The":[0,13,23,44],"research":[1],"establishes":[2],"a":[3,31,35,40,73,77],"neural":[4,49],"network":[5,50],"credit-risk":[6,51],"evaluation":[7,52],"model":[8,14,53],"by":[9,17],"using":[10],"back-propagation":[11],"algorithm.":[12],"is":[15,66],"evaluated":[16],"the":[18,48,60,81],"credits":[19],"for":[20],"120":[21,24],"applicants.":[22],"data":[25],"are":[26],"separated":[27],"in":[28],"three":[29],"groups:":[30],"\"good":[32],"credit\"":[33,37,42],"group,":[34],"\"middle":[36],"group":[38],"and":[39,76],"\"bad":[41],"group.":[43],"simulation":[45],"shows":[46],"that":[47,65],"has":[54],"higher":[55],"classification":[56],"accuracy":[57],"compared":[58],"with":[59],"traditional":[61],"parameter":[62],"statistical":[63],"approach,":[64],"linear":[67],"discriminant":[68],"analysis.":[69],"We":[70],"still":[71],"give":[72],"learning":[74],"algorithm":[75,79],"corresponding":[78],"of":[80],"model.":[82]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2016-06-24T00:00:00"}
