Insolvency prediction of irish companies using backpropagation and fuzzy ARTMAP neural networks

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

1 Citation (Scopus)

Abstract

This study explores experimentally the potential of BPNNs and Fuzzy ARTMAP neural networks to predict insolvency of Irish firms. We used financial information for Irish companies for a period of six years, preprocessed properly in order to be used with neural networks. Prediction results show that with certain network parameters the Fuzzy ARTMAP model outperforms BPNN. It outperforms also self-organising feature maps as reported by other studies that use the same dataset. Accuracy of predictions was validated by ROC analysis, AUC metrics, and leave-one-out cross-validation.

Original languageEnglish
Title of host publicationEnterprise Information Systems - 11th International Conference, ICEIS 2009, Proceedings
PublisherSpringer-Verlag
Pages287-298
Number of pages12
ISBN (Print)9783642013461
DOIs
Publication statusPublished - 2009
Event11th International Conference on Enterprise Information Systems, ICEIS 2009 - Milan, Italy
Duration: 6 May 200910 May 2009

Publication series

NameLecture Notes in Business Information Processing
Volume24 LNBIP
ISSN (Print)1865-1348

Conference

Conference11th International Conference on Enterprise Information Systems, ICEIS 2009
Country/TerritoryItaly
CityMilan
Period6/05/0910/05/09

Keywords

  • Backpropagation
  • Data mining
  • Fuzzy ARTMAP
  • Insolvency prediction
  • Neural networks

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