【摘要】 商业银行非现场监管在整个商业银行监管体系中占有中枢神经的地位.文章将商业银行非现场监管作为模式识别分类问题进行研究,提出了通过神经网络的建模,构造基于马哈拉诺比斯距离的联合判别模型的方法.并以实际数据为基础验证了模型的有效性,进行了商业银行分类识别.更多还原

【Abstract】 The off-site banking regulation system plays a key role in the entire banking regulation system. In this paper, we regard the off-site regulation as a kind of pattern recognition problem, and a new model based on neural network and Mahalanobiz distance discriminant analysis is presented. Using this model, we classified commercial bank from the practical data. In the model, the input vector is regulation indexes. The model training is carried on through BP arithmetic and Mahalanobiz distance discriminant analysis in order to reach a certain accurate rate. A new sample is the classes corresponding to neuron whose output vector has the minimal distance with the connection weight vector of neuron. The effectiveness of the proposed approach is clearly demonstrated by the experiment results.更多还原