sort algorithm 中文意思是什麼
sort algorithm
解釋
排序演算法-
The paper introduces a sort of encrypted algorithm which comparied with the original length of cryptograph, the length of encrypted cryptograph will base on the difference of the encrypted information piece length to minish
本文介紹了一種加密后的密文長度與原明文長度文相比，依據所選加密信息塊長度的不同而做相應減小的加密演算法。 -
A new algorithm is proposed that promises to deliver solutions to both the problems mentioned above, by using dual cluster head, which is very useful to minimize the use of epidemic algorithms of any sort, thereby saving a lot of resources and also making mute discovery more easier
本文提出一種能解決以上兩種問題的新演算法，即在演算法中使用雙簇首，可以減少任何形式的流行演算法的使用，因而節約了許多資源並且使得路由發現更容易。 -
Application of genetic algorithm in data mining has been studied. based on gene hypothesis gene dynamic sort method has been brought forward. its feature is component of genes can become longer and better gene component and because of dynamic sort, good gene component can be kept effectively
在分類規則提取系統中，為了更好地提高演算法的尋優和保優能力，提出了基因動態排序方法，即把各基因位按重要性大小進行排序，在此基礎上再進行交叉操作。 -
Science and technology text auto sort study base of svm and knn algorithm
演算法的科技文獻自動分類研究 -
Sorting algorithm can solve logic gate circuit for more fanout, more loop nestification and feedback alternately. we sort these nodes according to their joint relationship by the sort algorithm that can determine the priority order of digital circuit simulation and give the feedback chain
排序演算法可以解決具有多扇出、多迴路嵌套及交叉反饋的邏輯門電路，按照其連接關系進行排序，並給出其中的最大反饋鏈。 -
With the coming of information age, more and more people realize the importance of information. useful information hidden in plenty of data needs mining energently. the technology of data mining arises and develops unders such circumstance. the main tast of data mining is to extract or mine the useful information from the data. we can get great amount of data from the computer transaction every day. the data is very useful for us to make decisions on management. the paper concludes and introduces association rule about its concept, sort, model and step for mining the data, measure and some basic algorithm on the basis of the at research. at the same time, we analyse hopfield - network ' smodel, character, energy - function, movement - equation and so on. moreover, to the requirement of the system of information of computer - saling, we have done the following and there are good result. fisrt, considering the weight and constraint, we propose the algorithm for the weighted and constraint association rule
本文首先對數據挖掘中的關聯規則和神經網路的已有成果作了詳細深入的調研，歸納和整理了關聯規則的概念、分類、關聯規則挖掘的模型與步驟、關聯規則的度量方法以及一些基本演算法；還歸納和整理了hopfield網路的模型、特徵、能量函數、運動方程等，並在此基礎上，結合電腦賣場信息支持系統提出的需求，做了如下工作，並取得了一定的成果和成效： （ 1 ）考慮加權與約束兩種情況，提出了既帶權重又帶約束的關聯規則提取演算法。 -
In the clustered system, the data nodes have strong independency. in order to improve the concurrency, we put forward a sort of redundant array of independent data node ( raidn ), which is similar to raid 5. we also discuss its fault tolerant and propose a parity extension algorithm called sequence - extend
在我們提出的并行結構中，數據節點獨立性很強，為提高數據的並發度、負載平衡及容錯性，本文提出了一種類似raid5結構的獨立冗餘數據節點陣列raidn ，討論了系統的容錯性，並提出了一種稱為「順推法」的奇偶效驗位擴展演算法。 -
A group of multi - insertion sort algorithm
多插入排序演算法族 -
It allows the caller s code to become part of the sort algorithm
它允許調用方的代碼成為排序演算法的一部分。 -
The order of our discussions " about these tasks is as follows : firstly, we pay more attention to the characteristics and difficulties of its environment including the concept, typical system model, main challenges, mobile network connection and soft application. secondly, according to mobile specialties of the environment we make the sort of data into four kinds : general data, time series, spatial data and time - spatial data, and present general processing of data mining. lastly, we discuss the methods of data mining of these four kinds respectively : after the introduction of the actuality of data mining of every kind, an algorithm of rule updating based on rough set is given, then put forward the processing of data related to mobile users and flow chat according to characteristics of the other three kinds
本文對以上任務的討論順序安排如下：首先是對移動計算環境的技術特點和難點進行討論，包括移動計算的概念和典型系統模型、主要挑戰、移動聯網以及軟體應用這幾個大的方面；其次根據移動環境的移動特性把移動計算環境中的數據分為普通數據，時間數據，空間數據以及時空數據，提出了在移動計算環境中數據挖掘的一般流程；接下來分別對這四類數據進行挖掘演算法的討論：每一部分都是先介紹該類數據的挖掘方法研究現狀，對于普通數據，針對我們已提出的一種挖掘演算法-粗糙集演算法（ rs ） ，提出了對應的規則更新演算法，對於後三種數據，本人根據其在移動計算環境中的特點分別提出了與移動用戶相關的該類數據的一種具體的處理方法和演算法流程圖，包括基於移位連接方法的多屬性時間序列的挖掘演算法，基於apriori演算法的空間關聯規則數據挖掘方法以及關于移動用戶移動模式的時空數據挖掘方法，並用matlab對其中的規則更新演算法和時間序列的挖掘演算法這兩方面進行了實例模擬。 -
For detecting - analyzing method based on snapshot difference, we implement these snapshot differential algorithm : sort merge algorithm, partition hash algorithm and window algorithm. for detecting - analyzing method based on log, we discuss the analyzing method of log on two relation database systems - oracle and sql server
對基於快照差分的檢測分析方法，我們實現了三種快照差分演算法： sortmefge演算法、 partitionhash演算法和wndow演算法；對基於日誌的檢測分析方法，討論了oracle和sqlserver兩種關系數據庫的日誌分析方法。 -
The new merging sort algorithm by mapping
演算法的科研評審排序方法與應用 -
Search algorithm, definition of sort, insertion sort, quick sort, optimal sort time, merge sort, heap sort, radix sort, summarize of sort algorithms
搜索演算法；排序定義；插入排序；快速排序；最優排序時間；歸並排序；堆排序；基數排序；排序總結。 -
Wth regard to the threshold which used in the algoritlun based on wavelat transform and are determined by experience, we put forward a automatic and adaptive algorithm that can calculate the suitable threshold. this suggested algorithm makes use of the frequency analysis of the psychoacoustic model to make the embedded watermark inaudible. this idea can be used in such sort of watermark embedded algorithins based on wavelet transform
對于使用量化小波系數的加水印的演算法，對于其中要由經驗來確定的量化閾值，本文結合心理聲學模型的頻域分析，提出了一種自適應的求量化閾值的方法，這一方法對于其它使用小波變換加水印的演算法求閾值都有一定的參考價值。 -
Think about the locality of reference of the sort algorithm and the data you expect it to run on
考慮排序演算法的引用地址和預期其涉及的數據。 -
For example, a sort algorithm could be passed a reference to the method that compares two objects
例如，可以向排序演算法傳遞對比較兩個對象的方法的引用。 -
Moreover, the paper compiles a decision tree - making program by camm algorithm in matlab in order to compare with the clustering. regard the history fault data of gear case as specimen, at first the information gain of every decision property is calculated at current decision point and the decision property which has the greatest information gain is selected as the decision point. then the assembly is subdivided according to the value of its decision property. delete the groups whose degree of support for sort property classification is less then the designated value
以齒輪箱歷史故障數據為樣本，首先從當前決策節點計算每個決策屬性的信息增益，選擇具有最大信息增益的決策屬性作為決策節點，並根據該決策屬性的取值將該決策屬性所在集合分成若干個子集，濾掉所有子集中對類別標識屬性的分類支持度小於指定的最小支持度的元組，重復該過程直至生成決策樹。 -
Especially, in the latter model, the matched degree of system space and mission is taken as standards. and we also establish an index system and a model of c4isr system efficiency analysis correspondingly. after then some methods and algorithms are introduced, which include the principles and the method of choosing efficiency index and parameter index, the method of index filtering, the method of determining index function relation, the revising algorithm of ahp weight and the sort algorithm of judgment matrix
作者對國內外c ~ 4isr系統效能分析的主要方法進行了比較分析，提出了一種以指標體系為基礎的層次效能評估靜態模型和以系統空間與使命的匹配程度為目標的動態評估模型相結合的評估思想，建立了c ~ 4isr效能分析指標體系與模型，給出了性能指標與參量指標選取的原則與方法、指標篩選方法以及指標函數關系的確定方法、 ahp的權值修正演算法、含灰元的判斷矩陣排序演算法等。 -
The proposed algorithm for knapsack problem is based on mimd. the sort algorithm by sampling is introduced in the sorting stage. the stages of generating subset - sum and searching are also optimized
并行背包演算法基於mimd結構，在排序過程中引入基於采樣的排序演算法，然後對子集和生成和搜索過程加以優化。 -
In the paper an improved activity on vertex ( aov ) net is proposed to represent the alternative manufacturing processes route. it also raises a new overall topological sort algorithm. at last, based on the researching achievement above, an alternative computer aided process planning ( capp ) system is developed based on c / s structure, tested by the system, the researches above are validated
在多工藝方案的表示方法上，本文嘗試用一種復合式的活動點網（ aov ）來實現加工方法網路圖的表示，並且提出了一種活動點網（ aov ）網和復合式活動點網（ aov ）的全拓撲排序的演算法。
分享友人