收斂性的加速 的英文怎麼說

中文拼音 [shōuliǎnxìngdejiāsù]
收斂性的加速 英文
acceleration of convergence
  • 收 : Ⅰ動詞1 （把攤開的或分散的事物聚集、合攏） put away; take in 2 （收取） collect 3 （收割） harvest...
  • 斂 : Ⅰ動詞1 （收起; 收住） hold back; keep back 2 （約束） restrain 3 （收集; 徵收） gather; collect; ...
  • 性 : Ⅰ名詞1 （性格） nature; character; disposition 2 （性能; 性質） property; quality 3 （性別） sex ...
  • 的 : 4次方是 The fourth power of 2 is direction
  • 速 : Ⅰ形容詞（迅速; 快） fast; rapid; quick; speedy Ⅱ名詞1 （速度） speed; velocity 2 （姓氏） a surna...
  • 收斂 : 1 （減弱或消失） weaken or disappear 2 （約束言行） restrain oneself 3 [數學] convergence; constr...
  1. The preconditioned accelerate the convergence of 2ppj method

    型方法收斂性的加速
  2. And raga can steadily adjust and compress the variable changed space. the times of accelerating circle is not many, commonly, the times is under 10 times. even though the problem is very complicated, the times of accelerating circle is less than 50 times

    該方法具有處理復雜優化問題的能力，並且，它調整、壓縮搜索區間的性能也是穩健的，不易早熟收斂，加速循環的次數也不會很高，一般就在10次以下，即便是特別復雜的問題其加速循環次數也在50次以內，所以說raga的計算量很少。
  3. In order to quicken styptic v elocity, under - relaxation a nd source term linearization is appilied

    為了加快收斂的速度，採用了欠鬆弛技術和源項線性化。
  4. First, we consider an additive schwarz algorithm for the solution of ax 4 - f ( x ) 0, x when coefficient a is an m - matrix and f ' ( x ) 0. by applying the theory of weak regular splitting of matrices to the above considered algorithm, we obtain the weighted max - norrn bound for iterations. moreover, under the assumption that f ( x ) is concave, we establish monotone convergence of the considered algorithm

    本文內容如下：首先，應用加性schwarz演算法求解非線性互補問題，其中a是m陣，應用弱分解理論，我們獲得了在加權范數意義下誤差的幾何收斂速度，在f （ x ）是凹函數的假設下我們還獲得了此演算法的單調收斂性，同時我們給出此演算法的一種修改演算法，無需前面的假設，該演算法具有單調收斂性。
  5. A normal transform is introduced, and there are enough much grids in the region between the critical layer and the wall, where the variation of the disturbance is the quickest. the finite - difference of governing equations with fourth - order accuracy in the normal direction is utilized in full regions including points close the wall, and is very important for accurately discreting equations. the combination of global and local methods is implemented, and a new iterative formula is derived

    對于曲線坐標系下的拋物化穩定性方程，文中發展了求解的高效數值方法:引進法向變換，使得在臨界層與壁面之間的擾動量變化最快的區域有更多的法向網格點;導出包含邊界鄰域在內的完全四階精度的法向有限差分格式，這對方程精確離散至關重要;採用全局法和局部法相結合的方法及其新的迭代公式，大大加速收斂並得到更精確的特徵值。
  6. 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
  7. Abstract : based on the iterative bit - filling procedure, a computationally efficient bit and power allocation algorithm is presented. the algorithm improves the conventional bit - filling algorithms by maintaining only a subset of subcarriers for computation in each iteration, which reduces the complexity without any performance degradation. moreover, a modified algorithm with even lower complexity is developed, and equal power allocation is introduced as an initial allocation to accelerate its convergence. simulation results show that the modified algorithm achieves a considerable complexity reduction while causing only a minor drop in performance

    文摘:基於迭代的比特和功率分配機制，提出了一種低復雜度的比特和功率分配演算法.與傳統的迭代分配演算法不同，該演算法在每次迭代中只需要比較幾個特定的子載波.該方法在保持傳統迭代演算法性能的前提下極大地減小了迭代分配演算法的復雜度.此外，通過選擇等功率分配方案作為初始方案加快了演算法的收斂速度，進一步降低了演算法復雜度.模擬結果表明，提出的改進演算法在基本不犧牲系統性能的前提下有效地降低了演算法復雜度
  8. Anfis based on takagi and sugeno ' s fuzzy model has the advantage of being linear - in - parameter ; thus the conventional adaptive methods can be efficiently utilized to estimate its parameters

    由於節點參數是線性的，用梯度下降和最小二乘的混合學習演算法來調節參數，減少了運算量，加快了收斂速度。
  9. Laws of the new method were discussed in - depth by simulation and statistics, and the valuable result was acquired. such speeds the convergent velocity and boosts up its practicability

    同時，應用模擬程序及統計方法對智能登山法的規律作了細致深入的探討，獲得有價值的結果，使演算法的收斂速度加快，實用性增強。
  10. In this paper, we propose an improved evolutionary algorithm combining diversity maintaining mechanism and accelerating operators, which focuses on the contradiction between the maintenance of population diversity and search efficiency in solving multimodal function global optimization problem on a bounded area

    摘要針對演化演算法求解有界區域上的多峰函數全局優化問題中，保持種群多樣性和搜索效率的矛盾，提出了一種結合了多樣性維持機制和加速運算元的改進演化演算法並對演算法作了收斂性分析。
  11. Tests demonstrate that the using particle swarm optimization algorithm to optimize load distribution has the advantages of simpleness, fast speed and high degree of convergence, which can be generalized as a new method of rolling load distribution of tandem cold mill

    實驗證明，粒子群演算法在軋制負荷分配計算中，具有演算法實現簡便、運算速度快、收斂性好等優點，可以作為一種冷連軋軋制負荷分配的新方法加以推廣。
  12. A kind of complete convergence of sums for negatively associated sequences of non - identically distributed random variables, in the second chapter, is obtained and the requirement of known results are weakened to the condition that absoluted moment - larger than zero - is finite. the strong convergence of negatively associated sequences of non - identically distributed random variables is discussed in the third chapter. in the fourth chapter, after extend the laws of the iterated logarithm of strong stationary case to weak stationary case, we obtain the strong convergence rate for negatively associated sequences of non - identically distributed random variables in linear models

    其中第二章討論了一類不同分佈的na列的加權和的完全收斂性，我們把已有的結果對矩的要求放寬到了只要求大於0的絕對矩有限的情形；第三章討論了不同分佈的na列的加權和的強收斂性；第四章首先把文[ 10 ]的關于na的重對數律由強平穩的情形推廣到了弱平穩不同分佈的情形，然後得到了線性模型中不同分佈的na誤差列的收斂速度。
  13. To solve the polynomial equation ? ( z ) = 0, this paper proposes a simultaneous iteration and investigates its convergence and initial condition. it proves that the convergence has order 3 under the initial condition

    摘要採用文[ 1 - 3 ]中提到的加速方法，對經典的牛頓迭代法進行加速，得到了一個新的求多項式方程根的迭代法，主要對其收斂性進行了分析，得到了在較好的初始條件下該法是3階收斂的。
  14. Abstract : simulated annealing and multigroup parallel evolution are two helpful methods which can improve the performance of genetic algorithm. these two ideas are well combined in this paper, and a new algorithm is derived, that is the multigroup parallel genetic algorithm based on simulated annealing method. simulation results show that this method not only quickens the computation, but also improves the convergence efficiency, thus produces more satisfactory results

    文摘:模擬退火和多種群并行遺傳進化是兩種較好的改進遺傳演算法性能的方法.將這兩種思想有機地結合起來，提出了一種基於模擬退火機制的多種群并行遺傳演算法.模擬結果表明，該演算法不僅能增強演算法的全局收斂性，還能加快遺傳進化速度，得到滿意的全局最優值
  15. Pso is simple and efficient, so many researchers have been attracted by this algorithm, and furthermore, it converges fast by moving each particle aimed at guides when it deals with single - objective optimization, and these features are important in multi - objective optimization also. from some current research works, we describe a multi - objective particle swarm optimization algorithm ( mopso ) that incorporates the concept of the enhanced - dominance, we present this new concept to update the archive, the archiving technique can help us to maintain a sequence of well - spread solutions. a new particle update strategy and the mutation operator are shown to speed up convergence

    目前，國內外已有部分相關研究成果，但是它們在解集分佈性、收斂性方面仍存在不足，在吸取已有成果的基礎上，本文提出了一種改進的多目標粒子群演算法（ mopso ） ，使用我們提出的強支配概念構造外部種群，使解集保持良好的分佈性，同時，通過採用新的全局極值和個體極值的選取方式及採用新的種群更新策略加快解集的收斂，提出基於快速排序的非支配集構造方法加快演算法運行效率。
  16. In order to accelerate the convergence rate, we improve the original method with chebyshev polynomials and preconditioning techniques, and present two new algorithms

    為了加速子空間迭代法的收斂性，我們應用chebyshev多項式與預處理技術，得到了兩個新的改進演算法。
  17. Consequently, the convergence rate of the proposed method is superlinear. to speed up the method, we combine the structured mbfgs method with gauss - newton method to propose a hybrid method

    為了加快演算法的收斂速度，我們結合guass - newton法和結構化mbfgs法提出一種雜交方法，證明了這個雜交方法的全局收斂性。
  18. This algorithm makes use of these characteristics and is improved according to the practical characteristic of communication system. not only the early converge problem of genetic algorithm is avoid, but also the optimize solution in the colony is reserved. meanwhile mountain climbing performance of simulated annealing algorithm is used to improve the performance of genetic algorithm

    該演算法利用遺傳方法適于多變量數值求解、有較好的兼容性及模擬退火演算法有很好的加速性，結合通信系統的實際特點進行改進，不但避免了遺傳演算法的早熟收斂問題，同時使群體中的最優解得到了保留，並利用模擬退火演算法的爬山性能改善了遺傳演算法的性能。
  19. At the present time, the research in surface panel method is on the way from low - order to high - order for enhance the calculational precision and accelerate the non - linearity iterative convergence

    為了提高計算精度，加速非線性迭代的收斂性，面元法正沿著由低階向高階的方向發展。
  20. Second, for vector sequence coming from the steep - descent method, we use extrapolation method for the sequence and get some applied algorithms. we also give theoretical proofs for this algorithms. many numerical experiments tell us that the new algorithms sometimes can save 80 % computation

    其次，對求解非線性優化問題的最簡潔的最速下降方法產生的迭代序列，運用向量序列加速收斂手段進行了討論，導出了一些實用的加速演算法，並從理論上證明快速演算法的有效性，眾多數值試驗進一步表明：加速收斂的方法相比較加速前幾乎都能夠節約80以上的計算量。
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