Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (10): 58-59.
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苏晋荣 李兵义 王晓凯
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Abstract: This paper introduces the average information of individuals’ extreme value to the standard particle swarm optimization. This new method is tested with four functions and compared to another improved PSO. Experimental results indicate that the PSO put forward by this paper improves the search performance on precision, search speed and convergence rate.
摘要: 利用粒子群的平均信息,对基本粒子群算法进行了改进,对四种测试函数进行了函数优化仿真实验,并与其它改进的粒子群算法进行了比较,结果表明改进后的粒子群算法在精度及收敛率方面有明显提高。
苏晋荣 李兵义 王晓凯. 一种利用种群平均信息的粒子群优化算法[J]. 计算机工程与应用, 2007, 43(10): 58-59.
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http://cea.ceaj.org/EN/Y2007/V43/I10/58