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Research on System Identification by SPPSO Programming for Time-delay HBV Model
基于SPPSO算法的时滞HBV模型的系统辨识研究

Keywords: Time_delay Hepatitis B Virus dynamics model,Nonlincar systems identification,SPPSO
时滞的HIV动力学模型,非线性系统辫识,小种群粒子群优化算法

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Abstract:

Systems identification is an active research area of intelligent control theory. Existing algorithms like quadra- tic programming method can identify very limited parameter's number,has the limitations of stagnation and heavily de- pendent on initial values of the parameters. With the continuous development of the area of intelligent control, the de- grec of nonlinearity becomes higher and higher. But the method of nonlinear system identification has not formed a com- plete scientific theory system. Small population-based particle swarm optimization (SPPSO) is an optimization technique for locating the global optimum. SPPSO is easy to realize, quick convergence and effective. It can greatly reduce the time and resource costs in the processing of large data quantity of large-scale population problem. So,in system identifica- tion, especially in highly nonlinear and timcdelay system it is more meaningful, and this kind of complex system is typi- cal in medical system. SPPSO is used in solving timcdelay hepatitis B virus dynamics (HBV) model. It has good re- search and practical value.

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