cluster partition 中文意思是什麼
cluster partition
解釋
類分割-
Also, following the digital processing of these logs, the optimal discrimination functions for determination of different types of bioherm reservoirs are presented by means of optimal partition, cluster and regression methods
利用巖心和測井數據總結了生物礁各種類型的測井響應，提出了適合柴西地區生物礁儲集層的測井曲線特徵。 -
Abstract : according to the theory of difference analysis, this paper proposed using mixed - f statistic to determine the optimal class number of fuzzy cluster, and using fuzzy partition entropy to verify whether the class number is optimal, the optimal class number can be determined by the two statistics mentioned above correctly
文摘:根據方差分析理論，提出應用混合f統計量來確定最佳分類數，並應用模糊劃分熵來驗證最佳分類數的正確性，綜合運用上述兩個指標可以準確確定最佳聚類數。 -
The premise to assure qos is to provide sufficient resource to meet demands. we come up with a method to partition the resources of web cluster for each class with its resource demand and priority requirement taken for granted, where system processing time or average access rates is summed up for each class periodically and resource demands is evaluated with stretch factor as performance metric. also the nodes marked in number will be orderly assigned to the classes ordered in priorities, which helps to maintain data locality and improves memory cache hits
資源滿足需求是實現服務質量保證的前提，為滿足業務類動態的資源需求，我們提出一種支持業務類優先級和資源需求的資源劃分方法，通過按周期對業務類請求處理時間或平均訪問率進行統計，以響應擴展因子為質量指標對業務類預期的資源需求作出評估，採取按主機編號有序地分配給按優先級排序的業務類，減少業務類資源變動和提高主存cache命中率。 -
The paper puts forward the clustering algorithm includes : clustering based on grid and iterative, enhanced clustering algorithm base on density and k - medoids, enhanced k - means algorithm ( optimize chooseing consult _ points in iterative process ), enhanced clustering algorithm base on distance. they can overcome many limitations ( some traditional algorithms terminate in local optimization. many results of cluster are roundness, too many times in partition iterative process ), which are related to the static architecture of traditional model
在傳統聚類演算法的基礎上，結合我們科學數據挖掘的應用對象?分子動力學數據，提出了迭代網格聚類演算法， k -平均和基於密度結合的聚類演算法，迭代過程中優化選擇中心點的k -平均方法，以及改進型的基於距離的聚類演算法等模式識別方法，能夠解決傳統演算法帶來的諸多問題（比如一些傳統的聚類演算法常常收斂于局部最優，發現都模式都趨近於球形，劃分方法中迭代次數過多帶來的效率問題） 。 -
The most common partitioned environment consists of a single database partition on each physical system that makes up the database partition cluster
最常見的分區環境由每個物理系統上的一個數據庫分區組成，這些物理系統組成數據庫分區集群。 -
Incoming work for a partition is routed to the cluster member hosting the partition
分區的輸入工作路由至承載該分區的集群成員。 -
The important research is about the theory and methods of the cluster analysis in view of statistical theory, the theory and methods of fuzzy cluster analysis, the fkn " s structure and the fkn ' s study algorithm ( fkn, fuzzy kohonen network ) - the organic fusion of the fuzzy c - means algorithm and self - organized feature map neural network. the paper proposes the ifkn ( improved fkn ) on the basis of the hard classification idea and the soft classification idea, then carries on the cluster analysis of the artificial synthetic control chart time series through matlab program and tt ? cluster result matches the cluster result of the famous dataengine " s software of the intellectual data analysis and data mining from german mit company. finally, the paper discusses the applying of the cluster analysis to the control process, which can be widely applied to the pattern recognition of the parameter " s changing trend during the control process and the image partition processing, and utilizes the ifkn to recognize the thermotechnical parameter " s changing trend based on the engineering of clinker sintering rotary kiln automatic control system of guizhou " s aluminium factory, through which good effect is obtained
數據挖掘技術在商業領域中已廣泛使用，然而在工業過程式控制制中的應用卻極少，本文正是在這種背景下，對數據挖掘中的聚類分析方法及其在工業過程式控制制中的應用研究作了償試，重點研究了基於統計理論的聚類分析理論和方法，模糊聚類分析理論和方法及模糊kohonen網路（ fkn ）的結構與學習演算法，即模糊c ? ?均值演算法與自組織特徵映射神經網路（ kohonen網路）的有機融合，並根據硬分類思想及軟分類思想提出了改進的模糊kohonen網路（ ifkn ） ，通過matlab編程對人工合成控制時序圖數據集進行聚類分析，其聚類效果與當今廣泛使用的數掘挖掘軟體平臺，德國mit公司著名的dataengine智能數據分析和數掘挖掘軟體的聚類效果相當，最後，論述了聚類分析在控制中的應用，它可以用於過程式控制制中的參數變化趨勢的模式識別及圖象分割處理等具體應用中，並以貴州鋁廠熟料燒結回轉窯自動控制系統為工程背景，利用ifkn識別其熱工參量變化趨勢，取得了較理想的效果。 -
After studying various constraints, a constraint - based cluster using function partition based on angle dissimilarity, a partition sowntown means with least outspread tree method, and the quantity of customer ' s sale was forecasted by time - series analysis were presented. so, a series of cspr ( cluster sown town partition rule ) to manage lcc database was describe
為實現對滿足約束條件的聚類尋找適當的方法，作者在分析聚類約束條件的基礎上，提出運用基於角度相異度的函數劃分法處理地理位置的約束條件，用最小生成樹聚類分析方法生成滿足多項約束條件的聚類，用時間序列預測技術使客戶銷量約束條件趨于完善。 -
The author of this paper took part in the designing and implementing the ha system which realized autonomic computing - virtual operation environment, which based on the cluster, partition, policy to achieve the ha and self - management
本文作者參加了一個實現自律計算的高可用性系統- - - -虛擬操作環境（ virtualoperationenvironment ）系統的開發工作。 -
Abstract : an efficient partitioning algorithm for mixed - mode placement, extended - mffc - based partitioning, is presented. it combines the bottom - up clustering and the top - down partitioning together. to do this, designers can not only cluster cells considering logic dependency but also partition them aiming at min - cut. experimental results show that extended - mffc - based partitioning performs well in mixed - mode placement with big pre - designed blocks. by comparison with the famous partitioning package hmetis, this partitioning proves its remarkable function in mixed - mode placement
文摘:提出一種專用於帶有預設計模塊的混合模式布局的劃分演算法.它基於擴展的mffc結群演算法，結合自下而上的結群和自上而下的劃分為一體進行混和模式下的劃分.這樣不僅可以使劃分能夠考慮電路本身的邏輯依賴，而且可以得到很好的"最小割"劃分結果.實驗結果表明，這種劃分演算法在層次式混合模式布局流程里起到了顯著的作用.將此演算法和當今國際上著名的劃分包hmetis進行比較，結果表明此演算法有一定的優勢 -
According to the theory of difference analysis, this paper proposed using mixed - f statistic to determine the optimal class number of fuzzy cluster, and using fuzzy partition entropy to verify whether the class number is optimal, the optimal class number can be determined by the two statistics mentioned above correctly
根據方差分析理論，提出應用混合f統計量來確定最佳分類數，並應用模糊劃分熵來驗證最佳分類數的正確性，綜合運用上述兩個指標可以準確確定最佳聚類數。
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