基于案例推理的财务危机预测模型研究

Studies on the Prediction Model of Financial Crisis Based on Case-based Reasoning

建立K近邻法案例推理模型的关键在于属性权重的确定。本文使用遗传算法、Lo-gistic回归标准化系数法来确定属性权重,这样就可以避免使用层次分析法、德尔菲法确定权重带来的成本过高的弊端。本文使用我国上市公司376个样本进行财务危机预测分析,预测结果表明,案例推理模型预测准确率高于Logistic回归模型。

The key to establish the case-based reasoning model of K-nearest neighbor is to determine the attribute weights. In this paper we use genetic algorithm and logistic regression coefficient of standardization to determine the attribute weights, so that we can avoid the big cost of using Analytic Hierarchy Process and Delphi method. We established a case-based reasoning model of financial crisis by using 376 samples of Chinese Listed Companies. Compared this model with the logistic regression model, it can identify financial crisis more accurately than the logistic regression model.