The dynamic clustering algorithm is developed to update the clusters.
最后针对数据库的更新设计了动态聚类算法。
Proposed dynamic clustering algorithm has strong robustness in clustering of time series multi-dimensional data.
本文算法对于时序数据的聚类具有较强的鲁棒性。
A dynamic clustering algorithm was proposed based on consistent matrix of dependent function for time series multi-dimensional data.
根据时序立体数据的特点，提出了基于关联函数一致性矩阵的动态聚类算法。
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