The Application Based on Support Vector Machine Optimized  by Particle Swarm Optimization and Genetic Algorithm

MAN Chun-tao; LIU Bo; CAO Yong-cheng

doi:10.15938/j.jhust.2019.03.014

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The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm

更新时间：2026-08-31

- The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm
- Vol. 24, Issue 3, Pages: 87-92(2019)
- 作者机构：
  
  哈尔滨理工大学自动化学院,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：10.15938/j.jhust.2019.03.014
  CLC： TP183
- Published：2019
- 稿件说明：
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MAN Chun-tao, LIU Bo, CAO Yong-cheng. The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm[J]. 2019, 24(3): 87-92.
DOI：

MAN Chun-tao, LIU Bo, CAO Yong-cheng. The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm[J]. 2019, 24(3): 87-92. DOI： 10.15938/j.jhust.2019.03.014.

摘要

为了提高参数优化精度，研究将粒子群算法与支持向量机相结合，建立基于粒子群算法的支持向量机复杂过程系统稳态模型。在此基础上，为解决粒子群算法容易出现早熟收敛、搜索精度不高、在迭代的后期效率低、容易陷入局部极优点等问题，提出了引入遗传算法的改进粒子群算法。通过利用改进后的粒子群算法对支持向量机参数进行优化，并应用到青霉素发酵这一复杂工业系统。仿真结果表明，改进算法提高了工业产量，实现了对系统结果的优化。

Abstract

In order to improve the precision of the parameteroptimization

the research integrates the Particle Swarm Optimization Algorithmwith Support Vector Machine

and matches the experimental data

and thenestablishes a steadystate model of complex process system

which is based onParticle Swarm Optimization Algorithm and Support Vector Machine On the basisof this model

an improved Particle Swarm Optimization Algorithm introduced toGenetic Algorithm is proposed

in order to overcome the defects of ParticleSwarm. Optimization Algorithm about premature convergencesearching accuracy isnot high

the iterative efficiency is low in the late stage

trapping into thelocal optimization and so on. By making use of the improved Particle SwarmOptimization algorithm to optimize the parameters of Support Vector Machine

itis applied to the complex industrial system of penicillin fermentation.The simulation result shows that the optimized algorithm improves theindustrial outputs

and optimizes the system results.

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