迭代法最優化 的英文怎麼說

中文拼音 [diědàifǎzuìyōuhuà]
迭代法最優化 英文
iterative method optimization
  • 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...
  • 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...
  • 最 : 副詞（表示某種屬性超過所有同類的人或事物） most; best; worst; first; very; least; above all; -est
  1. Among hese method, one of the simplest is the deepest gradient descent algorithm, but it has one disadvantage that the solutions are oscillatory and slowly convergent. a friction term is ntroduced to avoid oscillatory solutions and raise convergence rate. the third major contribution of this dissertation is study on 3 - d diffuse object surface optical automatic measurement

    其次，結合要處理的具體問題，介紹數值優化及幾種常用的無約束最優化計算方法，以最優梯度法為基礎，討論其演算法的優缺點，通過引進阻尼系數，改進了演算法的收斂速度，從而提高迭代精度。
  2. This algorithm easily escapes from local optimal solution, have high searching efficiency, simple structure, convenient use. aiming at iteration, optimization and matlab optimization toolbox having low precision and difficulty to choose initial vector on acquiring nonlinear equations ’ solutions, equations ’ solution problem is translated into genetic algorithm optimization problem. nonlinear equations ’ usual genetic

    針對迭代法、最優法、 matlab最優化工具箱求解非線性方程組中存在求解精度不高及初始矢量難選等問題，將方程組求解問題轉化為遺傳演算法函數優化問題，建立了非線性方程組通用的遺傳演算法解法，並將其用於汽車滑行試驗數據處理中。
  3. When used in multidisciplinary environment, csso has several advantages over standard optimization method : reduction of the information transfer ; elimination of large iteration loop ; allowance of the use of corresponding subspace optimizers in different disciplinary analysis ; a parallel optimization architecture which is readily operable on a suite of heterogeneous equipments ; more natural fit to the current organization structure found in most institutes of aerospace and aeronautic design ; participation of the disciplinary experts to best deal with specific disciplinary models

    當應用於多學科設計環境時，并行子空間優化方法相對傳統優化方法有幾大優點：減少了學科間信息傳遞的數量；免去了大的迭代循環；允許在不同學科分析模塊中應用不同子空間優化器；可以在不同設備上并行運行；結構框架適用於傳統學科組織形式；允許各學科專家最大限度地參與學科分析和設計。
  4. On the condition that the width of section is invariable, the height of section is confirmed by structural optimization method. this will change traditional method to optimize the height of section so that design is simplified and cost is lower. this paper presents one optimization design method

    在給定抗滑樁截面寬度的條件下，運用結構優化的方法來確定抗滑樁截面高度，改變傳統的確定樁截面尺寸這一迭代計演算法，使抗滑樁截面高度取最優值，達到簡化設計和降低工程造價之目的。
  5. This paper exhausts fully adjustable factor which could amend the dynamic function in fuzzy control system, and that traditional algorithms select factors with intercession is easy to get a partial solution, so this paper presents a new method to select factors based on genetic algorithm. this method has a large range over covered the solutions which could benefit to search the best solutions. it has great character and advantage

    本文充分闡述了可調整因子在模糊控制中能夠改善了系統的動態性能，並根據傳統的優化演算法在選取控制因子時是從單個初始值迭代求取最優解的、很容易陷入局部最優解這一問題，提出了一種基於遺傳演算法的可調整因子的選取方法，這種方法覆蓋面比較大，有利於全局擇優。
  6. As for single objective optimization algorithm, a fast iterative algorithm based on conjugate gradient algorithm is presented, which makes use of extent limit of iterative optimization step in conjugate gradient with the idea of least square

    在標量優化圖像重建法中，作者以最小二乘為目標，利用共軛梯度法中迭代最優步長的區間性，提出了一種基於共軛梯度法的快速迭代演算法。
  7. The paper puts forward the clustering algorithm includes : clustering based on grid and iterative, enhanced clustering algorithm base on density and k - medoids, enhanced k - means algorithm ( optimize chooseing consult _ points in iterative process ), enhanced clustering algorithm base on distance. they can overcome many limitations ( some traditional algorithms terminate in local optimization. many results of cluster are roundness, too many times in partition iterative process ), which are related to the static architecture of traditional model

    在傳統聚類演算法的基礎上，結合我們科學數據挖掘的應用對象?分子動力學數據，提出了迭代網格聚類演算法， k -平均和基於密度結合的聚類演算法，迭代過程中優化選擇中心點的k -平均方法，以及改進型的基於距離的聚類演算法等模式識別方法，能夠解決傳統演算法帶來的諸多問題（比如一些傳統的聚類演算法常常收斂于局部最優，發現都模式都趨近於球形，劃分方法中迭代次數過多帶來的效率問題） 。
  8. And the repeated optimization method is a kind of climbing, so it ' s easy to convergent to local extermum. how to solve it is the problem that the paper will discuss

    另外，由於迭代最優化方法是一種爬山法，所以難免會收斂到局部極值，因此如何解決該問題也是本文將討論。
  9. As for repeated optimization method, the most important things are the chose of right clustering rules and the similarity measurement between clusters

    就迭代最優化方法而言，最重要的是選取適當的聚類準則和類間相似性度量。
  10. 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。
  11. In contrast to conventional optimization algorithms whose iterates are computed and analyzed deterministically, randomized methods rely on stochastic processes and random number / vector generation as part of the algorithm and / or its analysis

    傳統的最優化演算法中迭代的計算和分析是確定的，與之相比，隨機方法依靠隨機過程和隨機數字/向量的生成作為演算法和（或）演算法分析的一部分。
  12. The effective heat - transfer temperature difference ( t _ i ) of every effect of multi - effect evaporation subsystem and the preheat temperature rise ( t _ ( p, j ) ) of every level of multi - level preheat subsystem of the design model were distributed by equal heating area, equal heat - transfer temperature difference, and free proration methods. the simulation of design has been conducted by matrix method combined with iterative method. the free proration method transformed the decision variables from t _ i and t _ ( p, j ) with complex restriction into _ i 、 _ p, jwith the value range of 0 1, and provided a simple and convenient method for optimum design

    操作型模型分別以t _ 0 、 t _ k 、處理量f _ 0 、出料濃度x _ （ az ）等不同控制變量為未知變量並採用矩陣法結合迭代法進行操作模擬計算;在操作模擬計算的基礎上，建立了復雜多效蒸發系統操作優化模型，該模型以濃縮成本最小為優化目標，以t _ k和f _ 0為決策變量，採用遺傳演算法結合矩陣法求解。
  13. In conjugate gradient optimization algorithm, the continuous and digital models of an imaging system are defined to explain image acquisition, the image registration algorithm and the conjugate gradient reconstruction algorithm are designed

    在共軛梯度最優化迭代演算法中，對相機模型、圖像微位移和微旋轉角精確配準、共軛梯度重建等關鍵技術進行了研究。
  14. In the study, sd2000 spectrometer is applied to obtain radiation spectrum of flame within wavelength 480 - lloonm, from which flame temperature and monochromatic emissivity are derived by newton raphson non - linear method and levenberg - marquart modeling method. the flame monochromatic emissivity is translated in form of f ( / l ) and a ( a ) respectively

    在該方法中，採用sd2000型光纖光譜儀測量火焰在可見光（ 480 - 1100nm ）波長范圍內的火焰的輻射光譜，結合newton - raphson非線性迭代演算法和levenberg - marquardt最優化演算法，得到火焰溫度和單色輻射率變化規律。
  15. The fast spot price solution proposed in this paper introduces a decomposing model, which is benefit for analyzing each component of spot price. based on interior - point optimal power flow, which has superiority on calculating and decomposing spot prices under power market environment, after rational approximation, the coefficient matrix and its factor table of modifying equation are made constant and need no recalculation during iterations

    本文提出的快速實時電價演算法採用適于對實時電價各組成部分進行分析的分解模型，在內點法最優潮流的基礎上合理的常數化其修正方程系數矩陣，使其在每次迭代時不必重新計算，大大提高計算速度。
  16. In the image reconstruction based on optimization without constraint, the variable metric method, the steepest descent method, and conjugate gradient method were applied to image reconstruction to improve iterative efficiency and reconstructed quality, and their virtue and shortcoming were analyzed

    摘要在無約束最優化為基礎的圖像重建問題中，為了提高迭代效率以及重建圖像質量，首次提出將變度量法應用到圖像重建中。
  17. This paper researches and improves two important algorithms to reconstruct high resolution images, with reduced aliasing, from a sequences of undersampled rotated and shifted frames. the reconstructed image resolution is from two to four times higher than the undersampled frames

    本文研究和改進了運動補償迭代演算法和共軛梯度最優化迭代演算法，從欠采樣圖像序列中復原出高解析度的圖像，使被重建圖像的解析度比欠采樣幀提高了2 ~ 4倍。
  18. In this arithmetic, the objective function is modified gradually by distinguishing the rigid zone and plastic zone before carry through more calculation, in order to obtain the optimal solution of the programs. the convergence of the algorithm is also shown in this paper

    基於最優化理論及其求解方法，提出了一種求解塑性極限載荷的直接迭代演算法，通過逐步識別剛性區和塑性區，不斷修正目標函數，以逐步求得問題的最優解，論文證明了該優化演算法的收斂性。
  19. On the condition of the missing pixel information of the observed image during the process of imaging, based on the analysis of the degradation principle and establishment of the math model as well as discrete expression, this paper incorporates optimization method into the process of blur image restoration and proposes the deconvolution methods of non - zero background motion blurred image based on conjugate gradient optimization iteration

    摘要針對成像過程中觀測圖像存在像素灰度信息丟失的情況，在分析此類圖像的退化原理及建立其數學模型和離散化表達式的基礎上，將最優化方法中的共扼梯度法引入圖像復原過程中，提出基於共軛梯度優化迭代的非零背景運動模糊圖像去卷積方法。
  20. Among these algorithms, psm is the most stable and the most accurate one. 4 ) some problems existing in the early multi - resolution dynamic images analysis are discussed, and our solution is provided, which results in a new multiscale dynamic images analysis method. in those early methods, the coarse images will be discarded after they are processed

    當本文所提出的新的多尺度運動圖像分析方法形成之後，在mrf圖像分析過程中令人困擾的計算量很大的迭代最優化過程（即退火過程）被避免了，從而使我們的分析方法能夠更加精確和更加快速。
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