中文摘要：

针对标准粒子群算法收敛速度较慢、收敛精度较低、容易陷入局部最优等方面的缺点，提出一种融合细菌觅食算法和鲶鱼效应的混合粒子群算法。通过四个经典测试函数仿真实验，验证了该算法具有较其他改进方法更强的全局搜索能力、收敛速度和收敛精度。并针对一类可描述成Wiener模型的工业过程进行了参数辨识，通过数值仿真验证了混合粒子群算法的实用性以及较其他算法更强的非线性辨识能力。

英文摘要：

This paper put forward a new hybrid algorithm taking advantage of bacteria foraging optimization algorithm and the idea of catfish effect to transform its individual evolutionary strategies.It used the hybrid algorithm to test four classical func-tions and modelled Wiener simulation.The results show its superiority in the overall searching ability,convergence rate and so-lution precision than other improved PSO.