摘要
为了提高传统Z-Score财务预警模型的预警能力,本文将改进FOA算法的良好寻优能力和Z-Score财务预警模型相结合,提出了一种改进FOA算法的上市公司Z-Score财务预警模型.采用改进FOA算法来优化ZScore模型的参数,降低预测值和目标值之间的均方根误差(RMSE).经对选取上市公司财务数据的预测值和目标值对比,且检验其准确率.实验结果:传统的Z-Score模型、基本FOA算法优化Z-Score模型和改进FOA算法优化Z-Score模型的预测准确率分别为65%、70%和80%.实验表明改进的算法较大提升了Z-Score财务预警模型的预测能力,也表明了该算法的有效性.
In order to improve the prediction ability of the traditional Z-Score financial prediction model, this paper proposes a financial prediction model of Z-Score for listed companies based on improved Fruit fly Optimization Algorithm（FOA） by combining the good searching ability of improved FOA algorithm and the Z-Score financial prediction model. The Root Mean Square Error（RMSE） between the predicted value and target value is reduced by improved FOA algorithm being applied to optimize the parameters of Z-Score model. We compare the predicted value and target value of the financial data of listed companies to test the accuracy of financial prediction. The experimental results are as follows： accuracies of the traditional Z-Score financial prediction model, FOA algorithm optimized Z-Score model, and improved FOA algorithm optimized Z-Score model are 65%, 70%, and 80%, respectively. Experiments show that the improved algorithm significantly improves the predictive ability of Z-Score financial prediction model, it is also illustrated the validity of the algorithm.
作者
康彩红
王秋萍
肖燕婷
KANG Cai-Hong, WANG Qiu-Ping, XIAO Yan-Ting(Faculty of Sciences, Xi＇an University of Technology, Xi＇an 710054, China)
出处
《计算机系统应用》
2018年第11期198-204,共7页
Computer Systems & Applications
基金
国家自然科学基金青年科学资金(11601419)~~
关键词
果蝇优化算法
Z-SCORE模型
寻优能力
均方根误差
Fruit fly Optimization Algorithm（FOA）
Z-Score model
searching ability
root mean squared error
