| 粒子群算法在金融风险模型中的研究与改进 |
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| 引用本文： | 杨金辉,赵晋,马添翼,孙延风.粒子群算法在金融风险模型中的研究与改进[J].吉林大学学报(信息科学版),2008,26(2):192-198. |
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| 作者姓名： | 杨金辉 赵晋 马添翼 孙延风 |
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| 作者单位： | 1． 北京邮电大学 软件学院，北京 100876; 2． 中国标准化研究院 标准评估部，北京 100191 |
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| 摘 要： | 在一种非线性金融风险模型中引入粒子群算法，针对粒子群算法在迭代后期搜索能力不高、粒子容易陷
入局部最优的问题，基于对惯性权重的优化以及对每个粒子个体位置变异，提出一种改进后的粒子群算法。
利用粒子群算法选择最优控制参数，以最大程度降低金融系统的总风险值。仿真结果表明，改进后的粒子群算
法在全局最优以及搜索速度方面优于传统的粒子群算法。
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| 关 键 词： | 非线性 粒子群 风险控制 全局最优 |
| 文章编号： | 1671-5896(2008)02-0192-07 |
| 收稿时间： | 2019-09-11 |
| 修稿时间： | 2007年11月20 |
Financial Assessment of Listed Companies Based on PCA-SOM |
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| YANG Jin-hui,ZHAO Jin,MA Tian-yi,SUN Yan-feng.Financial Assessment of Listed Companies Based on PCA-SOM[J].Journal of Jilin University:Information Sci Ed,2008,26(2):192-198. |
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| Authors: | YANG Jin-hui ZHAO Jin MA Tian-yi SUN Yan-feng |
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| Institution: | 1． Software College，Beijing University of Posts and Telecommunications，Beijing 100876，China;
2． Standard Evaluation Department，China National Institute of Standardization，Beijing 100191，China
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| Abstract: | Particle swarm optimization algorithm is introduced into a nonlinear financial risk model to solve the
problem that particle swarm optimization algorithm has low search ability and particle is easy to fall into local
optimization at the later stage of iteration． based on the optimization of inertia weight and the variation of
individual position of each particle，an improved particle swarm optimization algorithm is proposed． PSO
(Particle Swarm Optimization) is used to select the optimal control parameters to reduce the total risk value of
the financial system to the greatest extent． The simulation results show that the improved particle swarm
optimization algorithm is superior to the traditional particle swarm optimization algorithm in terms of global
optimization and search speed． |
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| Keywords: | nonlinear particle swarm risk control global optimum |
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