With respect to the cluster problem of the evaluation information of mass customers in service management, a cluster algorithm of new Gaussian kernel FCM (fuzzy C-means) is proposed based on the idea of FCM. First, the paper defines a Euclidean distance formula between two data points and makes them cluster adaptively based on the distance classification approach and nearest neighbors in deleting relative data. Second, the defects of the FCM algorithm are analyzed, and a solution algorithm is designed based on the dual goals of obtaining a short distance between whole classes and long distances between different classes. Finally, an example is given to illustrate the results compared with the existing FCM algorithm.

中文翻译：

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服务资源分配的高斯核模糊C均值算法

针对服务管理中大客户评价信息的聚类问题，基于FCM的思想，提出了一种新的高斯核FCM（模糊C均值）聚类算法。首先，本文定义了两个数据点之间的欧几里得距离公式，并基于距离分类方法和最近邻在删除相关数据时使它们自适应聚类。其次，分析了FCM算法的缺陷，并基于获得全类之间的短距离和不同类之间的长距离的双重目标，设计了一种求解算法。最后，给出一个例子来说明与现有FCM算法相比的结果。