迭代點 的英文怎麼說

中文拼音 [diědàidiǎn]
迭代點 英文
iteration point
  • 迭 : Ⅰ動詞（輪流; 替換） alternate; change Ⅱ副詞1 （屢次） repeatedly; again and again 2 （及） in tim...
  • 代 : Ⅰ動詞1 （代替） take the place of; be in place of 2 （代理） act on behalf of; acting Ⅱ名詞1 （歷...
  • 點 : Ⅰ名詞1 （液體的小滴） drop （of liquid） 2 （細小的痕跡） spot; dot; speck 3 （漢字的筆畫「、」）...
  1. The procedure functions in the compare between partial image of dynamic collection and corresponding image of the airscape. in chapter 5, basing on the analysis of correlative theory of digital image, we introduce the improved fasted - down algorithm and simulative anneal algorithm, which applies to nn calculation, an d bring forward the unique and effective means, correlative original value evaluation. basing on the combination of correlative arithmetic, a stable, high - speed and exact correlative arithmetic is formed, which makes it possible to apply computer vision detection of single - needle quilting in industrial production

    本文展開研究並取得一定成效：構建了基於pci總線的微機實時圖像採集系統；在採集的布料總圖（鳥瞰圖）的基礎上，通過數字圖像的數字濾波、圖像增強、邊緣檢測等處理，提取布料圖像的邊緣，對輪廓的矢量化的象素點進行搜索，得到相應的圖案矢量圖，從而確定絎縫的加工軌跡，生成加工指令；在進給加工過程中，主計算機對動態局部圖像與總圖（鳥瞰圖）的對應部分進行圖像相關的匹配計算，應用數字圖像理論，結合神經網路計算的改進最速下降法和模擬退火演算法，提出獨特而有效的相關迭代初始值賦值方法，形成穩定、高速和準確的相關運算，實現單針絎縫視覺測量和自動控制。
  2. A new numerical procedure for analyzing the coupled vibration of a framed arch bridge with a single moving vehicle is presented to solve the equations of motion of a bridge with many degrees of freedom. the procedure consists in dividing the bridge - vehicle systems, which are solved separately, into 2 subsystems at the interface of the bridge and vehicle. the compatibility at the interface is obtained by an iterative procedure with aitken acceleration

    本文提出新的計算橋梁車激振動反應的方法，車?橋系統被分成兩個相互作用的子系統，這兩個子系統通過接觸點的協調條件耦合在一起，從而應用aiken動態加速法對橋梁運動方程、車輛運動方程和車?橋耦合方程進行高效迭代求解。
  3. Thirdly, from the idea of locally linear approximate, another tangent - plane algorithm is presented for the distance between the convex nurbs surfaces. the critical step is the construction of the support mapping by gjk and lc to search for nearest points, and emphases are laid on dealing with isotropic cases and choosing initial iterated points. it is also proved that no isotropism during iteration would take place if initial iterated points are positive points

    切平面法是運用gjk和lc構造支撐映射的原理而設計的一個搜索近點對的迭代法，著重給出了迷向情況的處理和初始迭代點的選取方法，並證明了只要將初始迭代點取為陽點，就不會出現迷向情況。
  4. The basic idea is to find iterative points which converge to optimal point and its corresponding objective function or merit function values converge to optimal value

    其基本思想是構造迭代點來逐步逼近最優點，相應的目標函數值或評價函數值逼近最優值。
  5. The parameter control methods are in the contrast, which is to find a sequence of parameters that converge to optimal value and its corresponding points in converge to optimal solution

    參數控制演算法的基本思想正好相反，它是構造參數序列來逼近最優值，相應的迭代點列逼近最優點。
  6. Secondly, the penalty coefficient may converge to infinity in many situations when the iterative point is closely near the bound of feasible set, while the parameters are bounded if the solution set of constrained optimization is nonempty, which is available for numerical computation

    另外在很多情況下，罰函數法中的罰因子當迭代點接近可行域邊界時趨于無窮大，而參數控制演算法中，只要約束優化問題有最優解，則參數是有界的，這對數值計算是有利的。
  7. Of course, the prerequisite for being able to making this shift is that although the trial step is unacceptable as next iterative point, it should provide a direction of sufficient descent

    當由信賴域子問題求得的搜索方向不被接受時，利用線搜技術得到接受步長，定義新的有足夠下降量的迭代點。
  8. We use a scaling matrix which make the algorithm generate sequences of point in trust region and the interior of the feasible set. because of the boundedness of the trust region, trust region algorithm can use non - convex approximate models

    構造合理的仿射變換矩陣，在投影空間構造信賴域子問題，產生迭代方向，使迭代點既保持在信賴域內，又是嚴格可行域的內點。
  9. Fan and yuan [ 6 ] uses another method that has proved under the local error bound condition, if we choice the parameter as the norm of the function, the sequence produced by the levenberg - marquardt method converges quadraticlly to a solution of the system of the equations

    如此選取參數有一些不足之處。范、袁在[ 6 ]中用另一種方法證明了當迭代參數為當前迭代點處函數值的模時， levenberg - marquardt方法具有二階收斂性。
  10. Recently, yamashita and fukushima [ 4 ] show that the sequence produced by the levenberg - marquardt method converges quadraticlly to the solution set of the equations, if the parameter is chosen as the quadratic norm of the function and under the weaker condition than the nonsingularity that the function provides a local error bound near the solution. however, the quadratic term has some unsatisfactory properties

    最近yamashita & fukushima [ 4 ]提出，在弱於非奇異性條件的局部誤差界條件下，如果選取的迭代參數為當前迭代點處函數值模的平方，則levenberg - marquardt方法產生的迭代點列二階收斂于方程組的解集。
  11. Here we consider the choice of the parameter as the norm of the gratitude of the function. we prove under the local error bound condition that the levenberg - marquardt method with this parameter converges quadraticlly to a solution of the system of the equations. and we also present two globally convergent levenberg - marquardt algorithms using line search techniques and trust region approach respectively

    我們提出選取迭代參數為當前迭代點處函數梯度的模，在局部誤差界條件下， levenberg - marquardt方法依然具有二階收斂性，並考慮了線搜索和信賴域技巧的levenberg - marquardt方法，分析了其全局收斂性。
  12. The smaller the value of the merit function is, the closer the iteration point is to the solution

    當價值函數的值越小時，迭代點越靠近最優解。
  13. This algorithm allows the search direction with only moderate accuracy, and does not require the feasibility of the iteration points

    該演算法允許搜索方向有相對較大的誤差，且不要求迭代點的可行性。
  14. The main task of traditional methods is to construct iterative points and that of parameter control methods is to find a sequence of parameters

    傳統演算法的關鍵是構造迭代點，而參數控制演算法的關鍵是構造參數序列。
  15. Without the strict feasibility of the initial points and iteration points, the algorithm is shown to possess both polynomial - time complexity and q - linear convergence

    該演算法不要求初始點及迭代點的可行性且具有q -線性收斂速度和多項式時間復雜性。
  16. The set of parameters is updated by using the information of the last iteration and brings about the centering effect towards the central path, which was called the self - adjusting effect

    這組參數利用上一個迭代點的信息對當前步向中心路徑進行調整，文中稱之為自調整作用。
  17. In general trust region method, a trial point is accepted as a new iterate and the procedure is repeated if the true reduction achieved by the objective function at this point is comparable with the reduction predicted by the quadratic model

    考慮到在一般的信賴域方法中，當目標函數沿該搜索方向的實際下降量和預計下降量擬合得比較好時，則由該搜索方向得到新的迭代點並調整信賴域半徑。
  18. For problems whose objective function or constraint functions have sharp curves on their contour maps ( such as the rosenbrock ' s function which has banana shape contours ), monotonicity may cause a series of very small steps, causing a huge number of iteration to reach their solutions. by using the nonmonotone technique, we get the sequence of successful interative point which should make the objective function mono - tonically decreasing. hence, we use both trust region strategy and line search technique and make each iterate generate an acceptable trial step in interior feasible set as next interative point

    我們利用非單調技術得到使目標函數非單調下降的迭代點，因為非單調克服高度非線性化函數的求解問題，從而避免了只使用單調搜索在「峽谷」現象局部最優解被卡的情況，我們用信賴域策略和非單調線搜索技術相結合的方法，使演算法產生的迭代步落在可行域內點，同時又在信賴域內滿足接受準則。
  19. Such methods are generally decreasing method, such as, feasible direction methods, constrained variable metric methods, etc. another class is sub - problems method, which approximates the optimal solution by solving a series of simple sub - problems, such as penalty function methods, trust region methods, and successive quadratic programming sub - problems, etc. the same property of two classes of methods is that they determine whether the next iterative point is " good " or " bad " by comparing the objective function value or merit function value at the current point and next iterative point

    另一類叫做子問題演算法，這種演算法是通過一系列簡單子問題的解來逼近原問題的最優解，如罰函數法、信賴域演算法、逐步二次規劃演算法等。這兩類演算法的一個共同特點是，通過比較當前點和下一個迭代點的目標函數值或評價函數值來確定迭代點的「優」或「劣」 ，若迭代點比當前點「優」則該迭代點可以被接受，否則須繼續搜索或調整子問題。
  20. Otherwise, the trust region radius is reduced and a new trial point is selected. it is possible that the region subproblem need to be resolved many times before obtaining an acceptable step, and hence the total computation for completing one iteration might be expensive. this article combines approximate trust region path and nonmonotonic backtracking strategy to solve nonlinear optimization subject to linear inequality constraints, that is, we use approximate trust region path to get the research direction by minimuming quadratical model in the trust region by employing

    本文在求解線性不等式約束優化問題時，將近似信賴域路徑與非單調信賴域方法相結合，即在信賴域半徑內沿近似信賴域路徑得到一極小化二次模型的搜索方向後採用回代法避免重復求解信賴域子問題，在此演算法中當搜索方向不被接受時，就用非單調線搜索技術得到接受步長，定義新的迭代點。
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