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。
However, the standard Particle Swarm Optimization is easy to fall into local optimum, and slow convergence.
然而，标准粒子群算法存在容易陷入局部最优，后期收敛过慢等问题。
In cluster analysis, Fuzzy K-Means (FKM) algorithm is one of the most widely used methods. However, FKM algorithm is much more sensitive to the initialization, and easy to fall into local optimum.
在聚类分析中，模糊k均值算法是目前应用最为广泛的方法之一，然而该算法对初始化敏感，容易陷入局部极值点。
应用推荐