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  • 标题:Artificial Neural Networks in the prediction of insolvency. A paradigm shift to traditional business practices recipes
  • 本地全文:下载
  • 作者:Marcia M. Lastre Valdes, Arlys M. Lastre Aleaga, Gelmar García Vidal
  • 期刊名称:Enfoque UTE
  • 印刷版ISSN:1390-9363
  • 电子版ISSN:1390-6542
  • 出版年度:2014
  • 期号:3310
  • 页码:38-58
  • 出版社:Universidad Tecnológica Equinoccial
  • 摘要:In this paper a review and analysis of the major theories and models that address the prediction of corporate bankruptcy and insolvency is made. Neural networks are a tool of most recent appearance, although in recent years have received considerable attention from the academic and professional world, and have started to be implemented in different models testing organizations insolvency based on neural computation. The purpose of this paper is to yield evidence of the usefulness of Artificial Neural Networks in the problem of bankruptcy prediction insolence or so compare its predictive ability with the methods commonly used in that context. The findings suggest that high predictive capabilities can be achieved using artificial neural networks, with qualitative and quantitative variables.
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