直接復示系統 的英文怎麼說

中文拼音 [zhíjiēfùshìxìtǒng]
直接復示系統 英文
direct repeating system
  • 直 : Ⅰ形容詞1 （成直線的; 硬挺的） straight; stiff 2 （跟地面垂直的; 從上到下的; 從前到后的） erect; v...
  • 接 : Ⅰ動詞1 （靠近;接觸） come into contact with; come close to 2 （連接; 使連接） connect; join; put ...
  • 復 : Ⅰ形容詞1 （重復） repeated; double; duplicate 2 （繁復） complex; compound Ⅱ動詞1 （轉過去或轉過...
  • 示 : Ⅰ動詞（擺出或指出使人知道; 表明） show; indicate; signify; instruct; notify Ⅱ名詞1 [書面語] （給...
  • 系 : 系動詞（打結; 扣） tie; fasten; do up; button up
  • 統 : Ⅰ名詞1 （事物間連續的關系） interconnected system 2 （衣服等的筒狀部分） any tube shaped part of ...
  • 直接 : direct; immediate
  • 系統 : 1. （按一定關系組成的同類事物） system 2. （有條理的;有系統的） systematic
  1. With the development of the network and the multi - processor system, the research, simulation and the impemeni of the system - level fault diagnosis which is the very important means to increase the reliability of the system, are becoming more and more important. on the system - leve1 fault diagnosis, based on the group theory of system - level fault diagnosis that has been put forward by pro f zhang, the paper constructs newly the theory bases, improves on the matrix method, reinforces and consummates group arithmetic of all kinds of test mode, for the first time, analyses and discusses the equation solution of all kinds of models, so al1 the consistent fault patterns ( cfp ) could be found, straightly and high efficiently, even if the sufficient and necessary condition of t - diagnosable is dissatisfied and the complexity of system - level fault diagnosis is greatly decreased, especialy in strong t - diagnosabl6 system. last the simulation system ' s function has been extended and the application hotspot and the development trend have been disscussed

    本人在張大方教授等人提出的基於集團的系統級故障診斷的理論基礎上，重新構建了系統級故障診斷的理論基礎，定義了系統級故障診斷測試模型的三值表示；改進了系統級故障診斷的矩陣方法，重新定義了測試矩陣、鄰接矩陣、結點對、結點對的相連運算、極大準集團和斜加矩陣，由此能直觀、簡便地生成集團和極大獨立點集；補充和完善了各類測試模型的系統級故障診斷的集團演算法，通過定義集團測試邊和絕對故障集，簡化了集團診斷圖，由此能較易地找到所有的相容故障模式，即使不滿足t -可診斷性，大大減少了系統級故障診斷的復雜度，尤其是對強t -可診斷系統；首次分析探討了各類測試模型的方程解決，由此從另一角度能系統地、高效率地求出所有的相容故障模式（ cfp ） ：擴充了系統級故障診斷模擬系統的功能，快速、直觀和隨機地模擬實驗運行環境，進行清晰和正確的診斷，同時提供大量的實驗數據用於理論研究，優化演算法和設計。
  2. The concept of otn node transmission model is introduced. the requirement of otn node transmission model is discussed. this model uses the frequency domain transmission matrix to express the otn node transport characteristics. the simplified model based on wdm and im - dd systems, the relationship between node characteristics and model parameters and measurement of model parameters are also discussed. at last a briefly discussion on how to develop the otn simulation and cad software based on our model is demonstrated

    在線性時不變的假設下，提出利用頻域傳輸矩陣來表示節點傳輸特性的方法給出了oxc和oadm兩類光傳送網節點的統一的表示根據目前通用的波分復用強度調制直接檢波系統的特點對復雜的頻域傳輸矩陣進行了簡化並對通常所關心的節點主要性能指標與模型參數的關系模型參數的測量和計算模型的設計與計算機模擬輔助設計軟體開發的銜接問題進行了討論。
  3. Both complicated and simple model of transient stability analysis are integrated in the software, applying the model of each component to different degree of precision respectively. joined with the power system diagram editor, the transient stability analysis can be carried out in a graphical way. some auxiliary models are introduced, such as the classes of fault information and swing curves, etc. these models turn out to be essential to make the procedure of transient stability simulation vivid and intuitionistic, with the swing curves of different variables during the transient period being showed and printed conveniently

    針對電力系統各元件模型的不同精確程度，採用成熟的數值解法實現了復雜模型的暫態穩定計算和簡化模型的暫態穩定計算，並與已有的面向對象的電力系統圖編輯器進行了很好的連接，實現了暫態穩定分析的圖形化；實現了故障信息類、變化曲線類等輔助對象，使得整個暫態穩定模擬計算的過程形象直觀，且能對暫態過程中各量的變化曲線進行方便地顯示和列印輸出。
  4. Svm is a kind of universal learning algorithm, which developed from statistical learning theory, that is, small sample learning theory proposed by vapnik. it can represent complicated functions especially in high dimensions, which can avoid the trouble of the dimension tragedy that happened in general algorithm. it also will not affect the system performance by using original data of the array for the eigenvector directly

    支持向量機是由vapnik等人提出的小樣本統計理論? ?統計學習理論發展而來的一種新的通用學習演算法，特別在高維空間中表示復雜函數，避免了常規演算法「維數災難」等麻煩問題，可直接用陣列原始數據作為特徵向量而不影響系統性能。
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