Application of PSO Algorithm in Parameter Optimization of Biodegradable Medical Polymer Degradation Model

The particle swarm optimization (PSO) algorithm is a stochastic global optimization technique based on swarm intelligence. It possesses advantages such as being a simple principle, few parameters and easy to be realized. In this paper, an optimization model is established to solve the difficulty in selecting parameters and improve the simulation accuracy of the biodegradable medical polymer degradation model. When modeling, the particle swarm optimization (PSO) algorithm is proposed to solve the model and calculate undetermined parameters of the biodegradable medical polymer degradation equations. A comparative analysis of the calculation results is progressed. It shows that parameters determined by optimization model make the simulation results of degradation model more close to the experiment results. Using this method to solve the model is more accurate and efficiency than determining parameters artificially. It also shows that the particle swarm optimization algorithm used to optimize parameters have practical significance and application value.