| 改进粒子群算法在支持向量机训练中的应用 |
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| 引用本文： | 田鹏,潘丰.改进粒子群算法在支持向量机训练中的应用[J].自动化技术与应用,2009,28(3):6-8. |
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| 作者姓名： | 田鹏 潘丰 |
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| 作者单位： | 江南大学,通信与控制工程学院,江苏,无锡,214122 |
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| 摘 要： | 训练支持向量机需要求解二次规划问题，LPSO算法对于求解含线性约束优化问题是一种直观、简单的方法。改进后的LPSO算法较好的解决了早熟收敛问题。对谷氨酸发酵过程建模的实验表明本文提出的方法训练精度高，泛化能力强。
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| 关 键 词： | 支持向量机 粒子群优化算法 线性约束优化 |
An Improved PSO Algorithm for Support Vector Machine Training |
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| TIAN Peng,PAN Feng.An Improved PSO Algorithm for Support Vector Machine Training[J].Techniques of Automation and Applications,2009,28(3):6-8. |
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| Authors: | TIAN Peng PAN Feng |
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| Affiliation: | ( School of Communication and Control Engineering, Jiangnan University, Wuxi 214122 China ) |
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| Abstract: | Training a Support Vector Machine requires solving a constrained quadratic programming problem. The Linear Particle Swarm Optimization （LPSO） algorithm is intuitive and simple to solve the constrained optimization problem. A modified LPSO algorithm is proposed to overcome the premature convergence problem. An application example on the Glutamic Acid fermentation process is also presented. |
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| Keywords: | Support Vector Machine Part icle Swarm Optimization linear constrained optimization |
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