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。

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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。

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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。

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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。

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