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计算机系统应用:2018,27(11):198-204
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基于改进FOA算法的上市公司Z-Score模型财务预警
康彩红, 王秋萍, 肖燕婷
(西安理工大学 理学院, 西安 710054)
Z-Score Model Financial Prediction for Listed Companies Based on Improved FOA Algorithm
KANG Cai-Hong, WANG Qiu-Ping, XIAO Yan-Ting
(Faculty of Sciences, Xi'an University of Technology, Xi'an 710054, China)
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投稿时间:2018-04-03    修订日期:2018-04-24
中文摘要: 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Z-Score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.
Abstract: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.
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基金项目:国家自然科学基金青年科学资金(11601419)
引用文本:
康彩红,王秋萍,肖燕婷.基于改进FOA算法的上市公司Z-Score模型财务预警.计算机系统应用,2018,27(11):198-204
KANG Cai-Hong,WANG Qiu-Ping,XIAO Yan-Ting.Z-Score Model Financial Prediction for Listed Companies Based on Improved FOA Algorithm.COMPUTER SYSTEMS APPLICATIONS,2018,27(11):198-204

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