内容：
制造业公司是我国市场经济的重要组成部分,判别分析制造业公司的财务风险对于进一步促进制造业实体经济健康发展具有重要现实意义。适当选取2013—2015年制造业公司为样本,利用SPSS统计软件运用主成分分析方法(PCA)对制造业公司的财务指标进行了筛选,再利用MATLAB软件借助粒子群算法(PSO)对支持向量机参数进行优选,构建了基于PSO-LIBSVM模型的公司财务风险预警模型。实证分析表明,该模型可以对制造业公司财务风险进行较为准确的度量,是将人工智能算法运用到经济管理领域的有效尝试,对分析公司财务风险具有一定的现实指导意义。 The manufacturing company is an important part of China's market economy. It is of great practical significance to judge the financial risk of the manufacturing company to further promote the healthy development of the manufacturing industry. (PCA) was used to screen the financial indexes of the manufacturing companies. The software of PSO was used to analyze the support vector machine (PSO) by means of particle swarm optimization (PSO). The support vector machine (PSO) was used to analyze the financial indexes of manufacturing companies. Parameters are optimized, and the corporate financial risk early warning model based on PSO-LIBSVM model is constructed. The empirical analysis shows that the model can make a more accurate measure of the financial risk of the manufacturing company, and it is an effective attempt to apply the artificial intelligence algorithm to the economic management field, which has certain practical significance to the analysis of the company's financial risk.

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