dynamic clustering method 中文意思是什麼

dynamic clustering method 解釋
動態聚類分析法
  • dynamic : adj 1 動力的，動力學的；力學（上）的；動（態）的；起動的。2 有力的，有生氣的；能動的；（工作）效...
  • clustering : 叢聚
  • method : n 1 方法，方式；順序。2 （思想、言談上的）條理，規律，秩序。3 【生物學】分類法。4 〈M 〉【戲劇】...
  1. 4. an object detection method with em ( expectation maximum ) algorithm of dynamic layer representations is researched and improved. previous algorithm contains optical flow computation, affined transformation, and clustering algorithm, and it is not convenient for detecting object quickly

    4 .分析並改進了基於em （ expectationmaximum ）演算法的運動目標分層檢測演算法，早期演算法由於涉及光流場求解、仿射變換、聚類合併等復雜運算，計算量大，不適合圖像序列的快速處理。
  2. 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
  3. Chapter 6 provide a study on the delivery network of port physical distribution system, and we define single physical distribution center location by the center - of - gravity method, multi - physical distribution center location by clustering - based method and dynamic physical distribution center location by dynamic programming model, and the lines of vehicles have been optimized by vehicles scheduling program ( vsp )

    第六章主要是探討港口物流系統的配送網路，運用重心法確定單個配送中心選址、分組法解決多個配送中心選址和動態規劃解決配送中心動態選址問題，並用里程節約法（ vsp法）對配送線路進行優化，尋找最佳運輸線路。
  4. 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

    儲層分級技術及經濟基底的確定：應用動態聚類方法，對儲層進行分類，並定義一個分級指數來對儲層的優劣進行評價，對研究地區兩口井的儲層進行了分級。
  5. On the basis of a evolving clustering method ( ecm ), a new modeling approach of t - s type dynamic fuzzy inference model is proposed

    摘要以一種進化聚類演算法（ ecm ）為基礎，提出了一種新的t - s型動態模糊推理模型的建模演算法。
  6. The planning methods are the weightiness method and dynamic clustering method

    樞紐型物流中心的規劃方法採用重要度法及動態聚類法。
  7. This paper in turn introduces correlative knowledge on case description and a object oriented representation, the aim, tenet of casebase organizing and index and a organizing and index method using dynamic clustering, several typical case retrieval methods, the acquirement of adjustment knowledge, the classification of adjustment methods and a transform adjustment model, evaluate method of new case and learning and maintenance of casebase etc. moreover this paper also stressed discusses two central problem in case retrieval : the setting of property weight and the assignment of local similar degree between property values

    本文依次介紹了案例表示的相關知識及一種面向對象的表示方法，案例庫組織索引的目標、原則及採用動態聚類進行組織索引的方法，幾種典型的案例檢索方法，案例調整知識的獲取、調整方法的分類及一個轉換式調整模型，新案例的評估方法及案例庫的學習與維護等。此外，對于案例檢索過程中的兩個重要問題，屬性權重的設置和屬性值間局部相似度的賦值問題作了重點討論。
  8. Weightiness method is, ordering the crunodes through comparing the weightiness of the crunodes. the main idea of dynamic clustering method is as follow : firstly, regard all the crunodes of planning region as clustering analytic swatches ; secondly, classify di fferent kinds of crunodes according to certain criterion, which must have typical traits ; finally, sort the crunodes by type

    而將動態聚類法應用於區域物流中心規劃的基本思路是：先將規劃區域中的所有結點視為聚類分析的樣本：再按一定的標準將樣本分為不同類，每一類具有典型的特徵，最後根據需要按重要程度逐類選擇結點。
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