dynamic clustering meaning in Chinese
动态聚类
Examples
- Websphere extended deployment provides autonomic capabilities - dynamic clusters and health monitoring - enabling websphere systems to adapt to changes in workload and health of the servers
Websphere extended deployment ( xd )提供动态集群和health monitoring的自主功能，以使得websphere系统能够适应伺服器的工作负载和执行状况的变化。 - A model for short term and super short term forecasting integrating neural network , expert system and dynamic clustering is introduced here , which involves weather , festival and other load forecasting affecting factors
介绍了一种整合神经网络、专家系统和动态聚类多种智能方法为一体的短期/超短期预测模型,综合考虑了气象、节假日等负荷影响因素。 - We found a new method to interpret log data under overpressure & high temperature based on the viewpoint . 3 . the reservoirs grading and the confirmation of economic floor : the paper classified the reservoirs using dynamic clustering and defined a grading factor to evaluate the reservoirs
储层分级技术及经济基底的确定：应用动态聚类方法，对储层进行分类，并定义一个分级指数来对储层的优劣进行评价，对研究地区两口井的储层进行了分级。 - From the angle of real estate development merchant , through a big amount of research and investigations , also based on consult lots of document means , the research mainly about the ways of cluster method , builds three mathematic models , such as blurring cluster analysis , dynamic cluster analysis , gray cluster analysis , the paper also has a further discussion about the practical application of models in making investment policy on real estate
论文从开发商的角度出发，通过大量的调查研究，查阅大量文献资料的基础上，重点围绕聚类方法展开研究，建立了模糊聚类分析、动态聚类分析、灰色聚类分析三个数学模型，探讨了模型在房地产投资决策中的实际应用。 - Following the two crows data mining process model , the product data , transaction data and customer ' s demographic data are accumulated , such data is preprocessed by the primary component analysis method which can low the connection of variants and reduce the number of variants . one model is built by the improved dynamic cluster method . the quality of the model ' s result will be improved with deleted the outlier data
参照twocrows数据挖掘过程模型，首先收集客户购买产品的类型、交易、属性等数据；然后采用主成分分析法预处理这些数据，以降低数据之间的相关性和减少变量个数；接着采用改进的动态聚类方法建模，在聚类过程中剔除异常点，改善聚类的质量，最终得到一个客户分片的模型，并对该模型作了比较详尽的解释。