Clustering provides an object auto-definition system, enabling the creation of WebSphere MQ messaging networks that are flexible during changes in topology.
集群机制提供一个对象自动定义系统，支持创建在拓扑变更期间保持灵活性的WebSphereMQ消息传递网络。
In general, and especially for Fabric clustering, it is important to create the object cache instances at the widest scope possible.
一般来讲，尤其是对于Fabric集群，在尽可能最广的范围内创建对象缓存实例是非常重要的。
Clustering is the process of grouping the physical or the abstract object set into classes or clusters.
所谓聚类，就是将物理或抽象对象的集合划分成为由类似的对象组成的多个类的过程。
Clustering process is a collection of physical or abstract objects into object classes similar to the process.
所谓聚类，就是将物理或抽象对象的集合分成相似的对象类的过程。
The chart of electron cloud can reveal the distance between each object and their clustering center.
电子云图的优点是可以反映每个对象与相应聚类中心的距离。
Based on clustering, a sliding window correlator algorithm for resolving the radar object ambiguity in range and velocity is described.
以聚类算法为基础，本文介绍了一种用于雷达目标解距离、速度模糊的滑窗相关器算法。
According to fuzzy clustering theory and fuzzy pattern recognition theory, a theory and model deciding forecast factor weight was present on basis of fuzzy object function in this paper.
根据模糊聚类与模糊识别理论，基于模糊环境下的目标函数，提出了一种确定预报因子权重的理论模式。
This system used an improved ant colony clustering algorithm to get hand center quickly, established relevant rendering system, and registered the virtual object.
利用一种改进的快速蚁群聚类算法来获取掌形的中心，建立相关的渲染坐标系，从而精确注册虚拟物体。
Traditional clustering method for attribute space ignores the object relationship information.
传统聚类算法仅考虑属性相似性，较少利用对象间的相互关系。
Fuzzy clustering is associated with comprehensive assessment in the study of sorting when the number of object is large, and we improve the method of setting up fuzzy similar matrix.
探讨了聚类分析这一重要的数据挖掘方法在综合评价中的应用，将模糊聚类与综合评价相结合以解决待评价方案数较多的排序问题，并且文中还改进了建立模糊相似矩阵的方法。
Finally, the precise contour of the object is extracted by the fusion of motion template and color clustering result.
最后，将运动目标的初始模板和彩色精确分割结合起来提取出具有精确边缘的运动目标。
For this issue we come out with a way to search the initial clustering point though distribution of data object, further more for assessing the clustering outcome accurately, a new way came out.
针对此问题，特提出了一种从数据对象分布出发寻找初始聚类中心的方法，而且为了准确评价聚类结果，还提出了一种基于数据对象的聚类评价方法。
For this issue we come out with a way to search the initial clustering point though distribution of data object, further more for assessing the clustering outcome accurately, a new way came out.
针对此问题，特提出了一种从数据对象分布出发寻找初始聚类中心的方法，而且为了准确评价聚类结果，还提出了一种基于数据对象的聚类评价方法。
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