基于熵法神经网络的金融系统危机预警模型分析

Yan Zhang
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引用次数: 2

摘要

为了提高金融系统的安全性,建立了基于熵值法的预警模型。分析了单因素模型、多因素模型、定量分析模型和定性分析模型。介绍了其优缺点。为后续的模型选择提供了理论依据。然后,设计后续模型的指标和样本。新模型的准确性、金融危机的渐进性和新指标都是假设的。结果表明,该神经网络模型在构建和预测方面都具有较好的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Financial System Crisis Early Warning Model Analysis Based on Neural Network with Entropy Method
In order to improve the security of the financial system, an early warning model based on the entropy method was established. Univariate models, multivariate models, quantitative analysis models, and qualitative analysis models were analyzed. The advantages and disadvantages were introduced. It provided the theoretical basis for the following model selection. After that, the indicators and samples of the follow-up model were designed. The accuracy of the new model, the gradual nature of the financial crisis and the new indicators were assumed. The results showed that the neural network model was relatively accurate in both construction and prediction.
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