聚類演算法 的英文怎麼說

中文拼音 [jùlèiyǎnsuànfǎ]
聚類演算法 英文
clustering algorithm
  • 聚 : 動詞（聚集; 聚積） assemble; gather; get together
  • 類 : Ⅰ名1 （許多相似或相同的事物的綜合; 種類） class; category; kind; type 2 （姓氏） a surname Ⅱ動詞...
  • 演 : 動詞1 （演變; 演化） develop; evolve 2 （發揮） deduce; elaborate 3 （依照程式練習或計算） drill;...
  • 算 : Ⅰ動詞1 （計算數目） calculate; reckon; compute; figure 2 （計算進去） include; count 3 （謀劃;計...
  • 法 : Ⅰ名詞1 （由國家制定或認可的行為規則的總稱） law 2 （方法; 方式） way; method; mode; means 3 （標...
  1. Finally, this thesis explored incremental algorithm, which featured normally in addable and non - iterative with some advantages, such as applicable to large and dynamic database, lower demand for memory, implementation of parallel processing and incremental update

    增量演算法的要求是聚類特徵一般是可加的、非迭代的，該文提出了一種基於密度的網格聚類演算法gdclus ，並在此基礎上提出了增量式演算法igdclus 。
  2. Based on the careful analysis of present clustering algorithm, we give two text clustering algorithms : ek ( exact k - means algorithm ) and dbtc ( density - based text clustering ), and discuss the results of clustering experiments

    對現有聚類演算法進行了仔細分析，給出了兩個文本聚類演算法： ek演算法和dbtc演算法。對這兩種演算法進行了詳細介紹，並分析了聚類實驗的結果。
  3. The experimental results show that the method can not only detect the fuzzy edge and exiguous edge correctly, but also improve the searching efficiency of fuzzy clustering algorithm based on tea evidently

    實驗結果表明，該演算法不僅具有很強的模糊邊緣和微細邊緣檢測能力，而且可以提高基於人工免疫進化演算法的模糊聚類演算法的搜索效率。
  4. Immune clone strategy is introduced into c - means algorithm, which can effectively tackle those problems of nonstability, slow convergence and nonideal clustering that exist in ids with the traditional c - means. the experimental results reveal that the system can detect variety of unknown abnormal intrusions, and demonstrate that our combined clustering algorithm has good performance

    實驗結果證明該上述兩種演算法有效地克服了傳統c -均值聚類演算法在解決入侵檢測問題中的穩定性差、收斂性不好和聚類效果不理想等問題，並能在一定程度上檢測到未知的異常入侵行為。
  5. Management data, boston, usa, 1984, pp. 47 - 54. 3 beckmann n, kriegel h - p, schneider r, seeger b. the r - tree : an efficient and robust access method for points and rectangles. in proc

    對cdt索引來說，首先高維數據點通過k平均聚類演算法得到若干類，然後分別計算該點對應的始點與質心距離，並且將這兩個距離通過線性組合得到該點的復合索引鍵值。
  6. Vector space model based on html document structure

    基於向量空間模型的文檔聚類演算法研究
  7. Based on some traditional algorithms, this thesis provides a weighted star cluster algorithm to learn user profile

    對已有演算法進行改進，提出了一種加權的星型聚類演算法以學習用戶的興趣特徵。
  8. To training the sample the article put forward a monitor type fuzz - c cluster arithmetic and using it to establish a standard pattern database. based on human cognize character, the article put forward a weightiness amend coefficient ( wac ) to denote the important extent of different character

    經過實驗驗證，本文提出了一組描述火焰圖像燃燒狀況的特徵參數，並採用一種改進的聚類演算法- -導師型模糊- c均值聚類演算法對標準模式做了訓練，建立了標準模式庫。
  9. This paper discusses the methods of similarity measurement of most clustering algorithms, and taking the type of attribute as a standard of choosing similarity, it expounds the methods used to measure numerical attribute, categorical attribute and mixed attribute

    討論了在大多數聚類演算法中的相似性測量方法，並以屬性的類型作為選擇相似性的標準，闡述了用於數值屬性，符號屬性及混合屬性相似性測量方法。
  10. Second, we design a chinese text clustering model ctcm and research main aspects of ctcm such as feature presentation, feature extraction, the adjust of feature vector and clustering algorithm. third, we lay emphasis on the study of text clustering algorithm

    然後，我們設計了一個中文文本聚類模型ctcm （ chinesetextclusteringmodel ） ，並針對模型中涉及到的特徵表示、特徵提取、特徵向量調整和聚類演算法等問題進行了研究。
  11. A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand. deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time, the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm. moreover, by introducing memory function and vaccine inoculation mechanism of immune system, at the same time, deca can converge to the optimal solution rapidly and stably. the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models. the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples, and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes

    針對模糊聚類演算法不適應復雜環境的問題，提出了一種新的動態進化聚類演算法，克服了傳統模糊聚類建模演算法須事先確定規則數的缺陷.通過改進的遺傳策略來優化染色體長度，實現對聚類個數進行全局尋優;利用fcm演算法加快聚類中心參數的收斂;並引入免疫系統的記憶功能和疫苗接種機理，使演算法能快速穩定地收斂到最優解.利用這種高效的動態聚類演算法辨識模糊模型，可同時得到合適的模糊規則數和準確的前提參數，將其應用於控制過程可獲得高精度的非線性模糊模型
  12. It has been improved, and specially proposed : firstly, we has increased run speed and ensure the diversity of population is with constructing non - dominated set by throwing off the dominated solutions, expressing the interior relation of individuals each other by the crowding distance, and constructing new population. secondly, we have further improved its convergence performance by clustering in precondition of ensuring a better distribution of individuals

    該文以nsga -為基準，對演算法進行了改進，具體提出了：用排除法構造非支配集、用聚集距離刻畫個體間的內部關系以及構造新群體，來提高運行速度和保持群體的多樣性；用聚類演算法在保持原有特性的前提下，進一步改善收斂性能等。
  13. Crowding model is used to form multiple niches in fitness landscape, while clustering algorithm eliminates genetic drift in each inner niche

    擁擠模型在適應值曲面上形成多個小生境，聚類演算法消除了每個小生境內部的基因漂移現象。
  14. In this text, we first do some research on the genetic algorithm about clustering, discuss about the way of coding and the construction of fitness function, analyze the influence that different genetic manipulation do to the effect of cluster algorithm. then analyze and research on the way that select the initial value in the k - means algorithm, we propose a mix clustering algorithm to improve the k - means algorithm by using genetic algorithm. first we use k - learning genetic algorithm to identify the number of the clusters, then use the clustering result of the genetic clustering algorithm as the initial cluster center of k - means clustering. these two steps are finished based on small database which equably sampling from the whole database, now we have known the number of the clusters and initial cluster center, finally we use k - means algorithm to finish the clustering on the whole database. because genetic algorithm search for the best solution by simulating the process of evolution, the most distinct trait of the algorithm is connotative parallelism and the ability to take advantage of the global information, so the algorithm take on strong steadiness, avoid getting into the local

    本文首先對聚類分析的遺傳演算法進行了研究，討論了聚類問題的編碼方式和適應度函數的構造方案與計算方法，分析了不同遺傳操作對聚類演算法的性能和聚類效果的影響意義。然後對k - means演算法中初值的選取方法進行了分析和研究，提出了一種基於遺傳演算法的k - means聚類改進（混合聚類演算法） ，在基於均勻采樣的小樣本集上用k值學習遺傳演算法確定聚類數k ，用遺傳聚類演算法的聚類結果作為k - means聚類的初始聚類中心，最後在已知初始聚類數和初始聚類中心的情況下用k - means演算法對完整數據集進行聚類。由於遺傳演算法是一種通過模擬自然進化過程搜索最優解的方法，其顯著特點是隱含并行性和對全局信息的有效利用的能力，所以新的改進演算法具有較強的穩健性，可避免陷入局部最優，大大提高聚類效果。
  15. On the improvement of k - means clustering algorithm

    均值聚類演算法的研究
  16. 3 ) k - mean clustering algorithm is used classification. the category is two, according to the object and the experience knowledge

    3 ）應用無監督分類演算法中k均值（ k - means ）聚類演算法對輸入特徵向量進行分類。
  17. The property of the recall - precision curve of a general retrieval algorithm and the k - means clustering method are used to realize the expansion according to the distance of image features of the initially retrieved images

    擴展主要利用了一般檢索演算法的查準率查全率曲線特點，對原始查詢結果的圖像特徵距離應用k -均值聚類演算法，確定多個查詢示例圖像。
  18. The kernel of the software consists of 4 clustering algorithms including pair - wise average linkage analysis, hierarchical clustering, self - organization feature mapping, and fuzzy clustering which is first applied in the field

    該軟體包含了兩兩平均連鎖聚類法、系統聚類法、自組織特徵映射法和模糊聚類等聚類演算法，其中模糊聚類演算法是首次用於基因表達模式分析。
  19. And then we propose two novel classification algorithms : k - cluster algorithm and synergetic fingerprint classification algorithm. here the second one is our main point

    隨后，提出了兩種新的分類演算法： k ?均值聚類演算法和協同指紋分類演算法。
  20. This article discussed the chinese word slice, character extraction, character expression and character matching methods, and established the chinese text classification and clustering algorithms based on neural network. in the design of chinese text mining based on web, the paper analyzed and researched the expression of web page information, structure feature, web page control symbol and html control symbol, and built the extraction flow of web page information, then gave two concrete application of chinese text mining based on web through combining with practical problems

    討論了文本分類中的中文詞切分、特徵提取、特徵表示、特徵匹配方法，建立了基於神經網路的中文文本分類、聚類演算法，在web中文文本信息挖掘的設計中，對網頁信息的表示、結構特點、網頁控制符、 html控制符號處理進行了詳細分析與研究，構建了網頁信息提取流程，並結合實際問題，給出了web環境下中文文本信息挖掘的兩個具體應用。
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