摘要
针对企业如何建立科学、准确的财务风险评价模型问题,文中将支持向量机的理论知识引入到财务数据的评估中。利用支持向量机解决小样本、非线性问题时,其具有较强泛化能力的优点,构建了支持向量机评估算法模型。为了改进支持向量机的性能,采用布谷鸟搜索算法对其进行优化,提高了向量机的检测精度。以某高校财务数据验证了该模型的可行性。测试结果表明,基于支持向量机的财务数据评估模型具有较高的精确度,能够解决财务数据的非线性问题,具有良好的应用价值。
Aiming at how to establish a scientific and accurate financial risk evaluation model for enterprises,the theoretical knowledge of support vector machines is introduced into the evaluation of financial data.Support vector machine has the advantage of strong generalization ability when solving small sample and nonlinear problems,and a support vector machine evaluation algorithm model is constructed.In order to improve the performance of the support vector machine,the cuckoo search algorithm is used to optimize it,and the detection accuracy of the vector machine is improved.The feasibility of the model is verified with actual financial data.The test results show that the financial data evaluation model based on support vector machine has high accuracy,can solve the nonlinear problem of financial data,and has good application value.
作者
过文俊
金恒
GUO Wenjun;JIN Heng(Xi’an Vocational and Technical College of Aeronautics and Astronautics,Xi’an 710089,China)
出处
《电子设计工程》
2021年第18期17-20,25,共5页
Electronic Design Engineering
基金
2019陕西省职业教育研究课题(SZJZD19-004)
西安航空职业技术学院2018年度教育教学改革研究项目(18XHJG-036)。
