tree sorting 中文意思是什麼
tree sorting
解釋
樹排序-
This thesis explains the necessity of the character recognition technology of the computer at first, describe the meaning in which the handwritten numeral discerns ; pretreatment technology of handwritten numeral recognition, including two value, line segmentation, word segmentation smooth, removing noising, standardization and thinning are discussed two value concretely discusses whole threshold value, some threshold value, dynamic threshold value and utilize space information to carry on threshold, which are several kinds of common method of choosing threshold value, especially utilize space information to carry on threshold value is describe in detail ; adopting to the foundation of thinning based on mathematics morphology, thinning algorithm of serials same and thinning algorithm of protecting shape are discussed ; afterwards, according to principle ' s diagram of the on - line character recognition, by analyzing the structure feature of the handwritten numeral, this thesis has proposed the online recognition te chnology of the free handwritten numeral based on the stroke feature and the online recognition technology of the free handwritten numeral based on the multistage classifying device. detail narrated noise removing, stroke characteristic definition and discernment, distance criterion of whole word match ; then under the foundation of handwritten numeral segmentation, off - line handwritten numeral recognition is researched. especially minimum distance classifying device, tree classifying device and adaptive resonance ( art ) network classifying device is discussed at the same time, believes degree analyses are introduced to integrate a lot of classifying devices ; at the end, the typical application of the handwritten numeral recognition was briefly narrated, its application in extensive data statistics, financial affairs, tax, finance and mail sorting have been explored
二值化時對整體閾值二值化、局部閾值二值化、動態閾值二值化和利用空間信息進行閾值選取幾種常用的閾值選取方法進行討論，特別對利用空間信息進行閾值選取進行了詳細論述；在對通過對基於數學形態學的細化的基礎上，討論序貫同倫形態細化演算法和保形的快速形態細化演算法；然後依據聯機字元識別原理框圖，分析了手寫數字的結構特點，提出了基於筆劃特徵的任意手寫數字在線識別技術和基於多級分類器任意手寫數字在線識別技術，對其中涉及的筆劃識別前的噪聲處理、筆劃間特徵量的定義及識別、整字匹配的距離準則進行了詳細敘述；繼而在對手寫數字的分割的基礎下對脫機手寫數字識別進行了研究，對基於最小距離分類器字元識別、基於樹分類器的字元識別、基於自適應共振（ art ）網路的字元識別分別進行了詳細討論，並引入置信度分析將多個分類器進行了混合集成；最後簡單闡述了手寫數字識別的典型應用，對其在大規模數據統計、財務、稅務、金融及郵件分揀中的應用進行了探索。 -
A red - black tree is a data structure and open technology that can be used for predefined priority - based sorting operations
紅黑樹是可用於預定義基於優先級的排序操作的數據結構和開放技術。 -
We denote many typical arithmetics with apla, such as, non - recursive tree traversals, dijkstra, topological sorting etc. the test result indicates the program transformer can improve the program ' s reliability and development efficiency. it can replace softeware blue collar to complete mechanical and creative work
5 、實現了自動轉換系統的泛型問題中的類型參數化問題，解決了apla提供泛型機制，而java語言不支持泛型機制的矛盾。 -
Followed by the rapid extension of data size, the usage of parallel technology is a very important method to improve the efficiency of data ming. sliq uses novel pre - sorting and breadth - first techniques to build a decision tree fast and accurately on a large data set, and can deal both categorical and numeric attributes. but the primary algorithm contains the abundant computing on attribute and record
本文首先分析了串列sliq演算法的原理和特點，針對其不足提出了一些改進方法，然後在基於pvm的環境下實現了演算法的并行化，分析了演算法的時間復雜度和加速比，提高了sliq演算法的效率，具有一定的理論意義和實用價值。 -
The construction algorithm embodies three parts that are suffix sorting, logest common prefix evaluation process and child suffix tree construction
整個建立演算法包括三個部分:后綴排序，計算最短公共前綴和建立子后綴樹。 -
Study on the algorithm of double identity tree - like data depth - sorting with recursion method
利用遞歸法實現雙編號樹形數據深度排序的演算法 -
Binary tree class - a binary tree is a data structure with nodes that include no more than two linked nodes. they are often used for sorting data
二叉樹是一個具有節點的數據結構，其每個節點最多包含兩個子節點。它們經常用來排序數據。 -
Super set of iemset x ) according to constrained subtree of itemset x, if item “ a ” isn ’ t a fuzzy item, we don ’ t scan database in addition. it can be generated by ffp tree. we propose two order methods for constructing ffp tree. one is that sorting database attributes holding frequent item in ascending order of their nodes number in ffp tree. another is that sorting frequent item of not fuzzy attributes in descending order of their support firstly, then sorting database fuzzy attributes with frequent item in ascending order of their nodes number in ffp tree. our experimental results show that although fmf needs more space costly than the algorithms based on apriori, its time costly is obviously lower than the latter
針對ffp -樹的生成，提出了兩種排序方法:按屬性順序將每個屬性下的頻繁項目依次插入到頭表中，屬性按照其在ffp -樹中可能的不同結點的個數從少到多進行排序;先對非模糊屬性下的頻繁項目按支持度從大到小進行排序，再對模糊屬性按其在ffp -樹中包含的不同結點的個數，從少到多進行排序，然後依次將各屬性下的頻繁項目插入到頭表中。
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