基于Elman_Adaboost算法的财务预警器的设计

The Design of the Financial Early Warning System Based on Elman-Adaboost

摘要: 为了有效的克服传统财务预测方法的局限性并进一步提高财务状况预测正确率，提出一种Adaboost算法和Elman神经网络的财务组合预测方法。该方法充分利用了Elman网络的动态特性和Adaboost算法能提高弱预测器精度的特性来提升预测的精度。通过对某上市公司财务数据的分析，结果证明，该方法经济有效，较大程度的提升了预测精度，并能够及时、合理地反映财务数据的危机状态。

Abstract: In order to effectively overcome the limitations of traditional financial forecasting methods and further improve the accuracy of financial situation prediction, a financial combination forecasting method based on Adaboost algorithm and Elman neural network is proposed. This method makes full use of the dynamic characteristics of Elman network and Adaboost algorithm can improve the accuracy of weak predictors to improve the accuracy of prediction. Through the analysis of the financial data of a listed company, the results show that the method proposed in this paper is economical and effective, improves the prediction accuracy to a great extent, and can reflect the crisis state of financial data timely and reasonably.