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计算机工程 ›› 2012, Vol. 38 ›› Issue (01): 174-176,179. doi: 10.3969/j.issn.1000-3428.2012.01.055

• 人工智能及识别技术 • 上一篇    下一篇

基于CBR与灰色关联度的财务危机预警

廖志文   

  1. (南开大学经济学院,天津 300071)
  • 收稿日期:2011-08-31 出版日期:2012-01-05 发布日期:2012-01-05
  • 作者简介:廖志文(1962-),男,博士研究生,主研方向:数据挖掘,人工智能

Financial Distress Pre-warning Based on CBR and Gray Correlation Degree

LIAO Zhi-wen   

  1. (School of Economics, Nankai University, Tianjin 300071, China)
  • Received:2011-08-31 Online:2012-01-05 Published:2012-01-05

摘要: 提出一种基于案例推理(CBR)与灰色关联度的企业财务危机预警模型。将灰色关联分析应用于企业财务危机预警的案例推理中,采用特征属性的主客观权重计算案例相似度。根据各特征属性对案例检索的重要程度,通过权重向量排除非关键指标对案例判断的干扰。实验结果表明,该方法得到的案例相似性排序结果符合实际情况,可提高相似企业的检索效率,满足企业财务危机预警的要求。

关键词: 财务危机预警, 灰色关联度, 案例检索, 属性权重, 相似度

Abstract: This paper proposes a financial distress pre-warning model based on Case-based Reasoning(CBR) and gray correlation degree. The method applies the gray relational analysis into CBR for business financial distress warning. The subjective and objective weights of characteristic properties are used to compute case similarity, which reflects the real similarity match. According to the important degree of each feature attribute to case retrieval, through the weight vectors remove interference for non-critical index to judge the case. Experimental results show that the sorting results of case similarity derived by the approach meet the actual situation and improve the retrieval efficiency of similar enterprises, it satisfies requirements of financial distress pre-warning.

Key words: financial distress pre-warning, gray correlation degree, case retrieval, attribute weight, similarity degree

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