基于粒子群优化的高职院校财务数据分析及预警模型研究

Kai Liu, Faqiang Cui
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引用次数: 0

摘要

本文提出了一种基于最小二乘支持向量机的职业学校财务预警模型。在模型中,相关数据由粒子群算法提供。通过设计合适的验证绩效指标,利用粒子群优化方法,优化向量机的相关值,使乘法最小化,并通过上市公司数据,对高职院校财务分析进行验证。仿真结果表明,该方法的仿真精度令人满意,且方法合理、高效。
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Research on Financial Data Analysis and Early Warning Model of Vocational Colleges Based on Particle Swarm Optimization
A financial early warning model of vocational schools is proposed in this study based on the least squares support vector machine. In the model, the relevant data is provided by particle swarm optimization. By designing appropriate verification performance indicators and using the particle swarm optimization method, the correlation value of the vector machine was optimized for minimizing the multiplication, and through the data of listed companies, the financial analysis of vocational colleges was verified. The simulation results showed that the simulation accuracy of the method was satisfactory, and the method was also reasonable and efficient.
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