The constriction factor Particle Swarm Optimization(PSO) algorithm is easily trapped in the local optimum and appeared premature convergence.
收缩因子粒子群优化算法容易陷入局部最优并出现早熟收敛的现象。
参考来源 - 一种克服局部最优的收缩因子PSO算法K-means algorithm is simple and fast,however its result is affected by the initial clustering center and easily falls into the local optimum.
K均值算法简单快速,但其结果容易受初始聚类中心影响,并且容易陷入局部极值。
参考来源 - 基于免疫粒子群优化的聚类算法·2,447,543篇论文数据,部分数据来源于NoteExpress
That they are easy to fall into a local optimum is the shortcoming of conventional optimization methods.
传统的优化方法,即所谓的确定性优化方法的突出缺陷是容易陷入局部最优解。
Otherwise, the hybrid algorithm can avoid trapping in local optimum and does not need initial feasible solution.
另外,该算法可有效避免陷入局部最优,也不要求提供初始可行解。
The experimental result indicates that the modified PSO increases the ability to break away from the local optimum.
实验结果表明,改进后的粒子群算法防止陷入局部最优的能力有了明显的增强。
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