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| Parameter optimization of polymer materials degradation model based on improved PSO algorithm |
| 1.School of Computer ＆ Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China; 2.Qinggong College, Hebei United University, Tangshan, Hebei 063000, China; 3.Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100190, China |
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Abstract To improve simulation accuracy of biodegradable polymer materials degradation model, a mathematical optimization model based on the actual principles in degradation of polymer materials and various factors was proposed. The particle swarm optimization (PSO) was used to optimize model parameters. To solve the weakness of standard particle swarm optimization algorithm, an improved algorithm was proposed to achieve optimization values. Dynamic adaptive inertia weight and asynchronous timevarying learning factors were introduced into the improved algorithm. The improved PSO algorithm was tested by five standard test functions to optimize the model parameters. The test and experiment results show that the proposed algorithm can effectively avoid being trapped in local minimum with increased accuracy and convergence rate. The simulation accuracy of biodegradable polymer materials degradation model can be significantly improved by optimized parameters. The algorithm is suitable to demonstrate the degradation mechanization and to guide the design and product of medical devices.
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2012, Vol. 33 
