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中文摘要：
针对数据流上的聚类任务受到时间、空间限制等问题,该文提出一种基于权值衰减的数据流模糊微簇聚类算法（WDSMC）。该算法使用改进的带权值的模糊C均值算法进行处理,并采用微簇结构和权值时间衰减结构提高聚类质量。实验表明,相对于现有的数据流加权模糊C均值聚类（SWFCM）算法和Stream KM＋＋算法而言,WDSMC算法具有更好的聚类精度。
英文摘要：
There is a great challenge in the data stream clustering due to a limitation of time and space. In order to solve this problem, a new fuzzy-clustering algorithm, called Weight Decay Streaming Micro Clustering （WDSMC）, is presented in this paper. The algorithm uses a reformed weighted Fuzzy C-Means （FCM） algorithm, and improves the quality of clustering by the structures of micro-clusters and weight-decay. Experimental results show that this algorithm has better accuracy than Stream Weight Fuzzy C-Means （SWFCM） and StreamKM＋＋ algorithm.
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