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.