Considering that the particle swarm optimization (PSO) algorithm is quite simple and easy to implement, it was used to estimate the nonlinear model parameters in this paper.
粒子群算法操作简便、容易实现且全局搜索功能较强，适用于非线性参数估计。
It selects the optimaler number as a global optimum at every circulation, which makes its result be better than both PSO and GA, then improves the overall performance of the algorithm.
与其他混合最优化算法不同的是，该算法没有破坏粒子群和遗传算法的独立性，而是仅通过全局最优样本把两个算法结合在一起。
PSO has been proved to be an effective global optimization algorithm. It is easy to implement, quickly convergence, and has been successfully applied to many engineering fields.
粒子群算法已经被证明是一种有效的全局优化算法，其收敛速度快，易于实现，已经成功地运用到了许多工程领域。
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