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dynamic clustering造句

"dynamic clustering"是什么意思   

例句與造句

  1. The second concept is dynamic cluster
    第二個概念是“動態(tài)集群” 。
  2. Manual mode only for dynamic clusters
    手動樣式(僅用于動態(tài)集群)
  3. This is done when you define the node group or dynamic cluster
    在定義節(jié)點(diǎn)組或動態(tài)集群時就完成了這一工作。
  4. The planning methods are the weightiness method and dynamic clustering method
    樞紐型物流中心的規(guī)劃方法采用重要度法及動態(tài)聚類法。
  5. Machines in the node group , essentially defining the maximum possible size for the dynamic cluster
    機(jī)器上配置服務(wù)器,這實(shí)質(zhì)上定義了動態(tài)集群的最大可能大小。
  6. It's difficult to find dynamic clustering in a sentence. 用dynamic clustering造句挺難的
  7. Residential electricity consumption load forecasting based on dynamic clustering and partial least - squares regression
    基于動態(tài)聚類與偏最小二乘回歸分析的居民用電負(fù)荷預(yù)測
  8. Projection pursuit dynamic cluster model and its application to evaluation of ecological quality of sichuan province
    投影尋蹤動態(tài)聚類方法及其在四川省生態(tài)環(huán)境質(zhì)量評價中的應(yīng)用
  9. Websphere extended deployment does this through a server template that is stored with each dynamic cluster
    Websphere extended deployment通過一個與每個動態(tài)集群( dc )一起存儲的服務(wù)器模板來完成這一工作。
  10. A dynamic cluster is similar to a regular websphere cluster , except the members of the dc are created and controlled by websphere extended deployment
    動態(tài)群集( dc )與正常的websphere集群類似,唯一的不同之處在于, dc的成員是由websphere extended depolyment創(chuàng)建和控制的。
  11. Websphere extended deployment provides autonomic capabilities - dynamic clusters and health monitoring - to enable websphere systems to adapt to changes in workload and health of the servers
    Websphere extended deployment ( xd )提供自主功能動態(tài)集群和health monitoring以使得websphere系統(tǒng)能夠適應(yīng)伺服器的工作負(fù)載和執(zhí)行狀況的變化。
  12. 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 )提供動態(tài)集群和health monitoring的自主功能,以使得websphere系統(tǒng)能夠適應(yīng)伺服器的工作負(fù)載和執(zhí)行狀況的變化。
  13. 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
    介紹了一種整合神經(jīng)網(wǎng)絡(luò)、專家系統(tǒng)和動態(tài)聚類多種智能方法為一體的短期/超短期預(yù)測模型,綜合考慮了氣象、節(jié)假日等負(fù)荷影響因素。
  14. 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
    儲層分級技術(shù)及經(jīng)濟(jì)基底的確定:應(yīng)用動態(tài)聚類方法,對儲層進(jìn)行分類,并定義一個分級指數(shù)來對儲層的優(yōu)劣進(jìn)行評價,對研究地區(qū)兩口井的儲層進(jìn)行了分級。
  15. 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
    論文從開發(fā)商的角度出發(fā),通過大量的調(diào)查研究,查閱大量文獻(xiàn)資料的基礎(chǔ)上,重點(diǎn)圍繞聚類方法展開研究,建立了模糊聚類分析、動態(tài)聚類分析、灰色聚類分析三個數(shù)學(xué)模型,探討了模型在房地產(chǎn)投資決策中的實(shí)際應(yīng)用。
  16. 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
    參照twocrows數(shù)據(jù)挖掘過程模型,首先收集客戶購買產(chǎn)品的類型、交易、屬性等數(shù)據(jù);然后采用主成分分析法預(yù)處理這些數(shù)據(jù),以降低數(shù)據(jù)之間的相關(guān)性和減少變量個數(shù);接著采用改進(jìn)的動態(tài)聚類方法建模,在聚類過程中剔除異常點(diǎn),改善聚類的質(zhì)量,最終得到一個客戶分片的模型,并對該模型作了比較詳盡的解釋。
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