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Business Failure Prediction Model based on Grey Prediction and Rough Set Theory

机译:基于灰色预测和粗糙集理论的业务失败预测模型

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摘要

A lot of methods have been used in the past for the prediction of failure business like Discriminant analysis, Logit analysis, Quadratic Function etc. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt, they endure some limitations, often due to the unrealistic assumption of statistical hypotheses. This is why we have undertaken a hybrid advisable system aiming at weakening these limitations. A hybrid model that predicts the failure firms based on the past financial performance data, combining grey prediction and rough set approach is possible to predict using few data and quickly calculate. The results are very encouraging, compared with original rough set, and prove the usefulness and highlight the effectiveness of the proposed method for firm failure prediction.
机译:过去,已使用很多方法来预测故障业务,例如判别分析,Logit分析,二次函数等。尽管其中一些方法导致模型具有令人满意的区分健康和破产能力的能力,但它们仍存在一些局限性,通常是由于统计假设的不现实假设所致。这就是为什么我们采取了旨在降低这些限制的混合建议系统的原因。可以基于过去的财务绩效数据预测失败公司的混合模型,将灰色预测和粗糙集方法相结合,可以使用很少的数据进行预测并快速进行计算。与原始的粗糙集相比,结果令人鼓舞,并证明了该方法的有效性并突出了所提出的方法用于企业故障预测的有效性。

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