最多迭代次數 的英文怎麼說

中文拼音 [zuìduōdiědàicìshǔ]
最多迭代次數 英文
maximum iterations
  • 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
  • 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...
  • 次 : Ⅰ名詞1 （次序; 等第） order; sequence 2 [書面語] （出外遠行時停留的處所） stopping place on a jou...
  • 數 : 數副詞（屢次） frequently; repeatedly
  • 最多 : at most; maximum
  • 次數 : number of times; frequency
  1. In the study of the lumber carrier, one of the very important problem is the in spot and ultimate station due to flooding which will bring tremendous threat to the ship because of the few holds in order to study the lumber carrier buoyancy, stability and longitudinal strength under the condition of flooding, the paper adopt fundamental ship principle and iterative and accumulative concept on the basis of insumersibility theory to detailedly calculate the flooding speed flooding amount front draft after draft stability and longitudinal strength considering the ship " s sinking and inclination which will change the center of gravity and the loading station both in hold and on deck and the effect of flooding and lumber amount in holdo in the last, the paper introduces an example of the actual ship named " fei yun ling " and makes a contrast between not taking measure and taking measure which draws a reasonable conclusion and comes up to some advice the method avoids the cockamamie calculating while insures enough precision the paper draws a conclusion that not all the lumber carrier will submerge when suffering the damaged flooding if the loading or measure is suitable

    為了研究運木船舶在破艙狀態下的浮性、穩性和強度，本文在抗沉性理論的基礎上，運用船舶基本原理，採用了迭代和累計的思想，將船舶的進水過程劃分為很多次進水的積累，詳細計算了運木船在破艙進水的過程中，考慮到各種破艙參數、船舶本身的下沉、艙室內木材、甲板貨的裝載情況和在進水過程中船舶本身的傾斜對進水重心的影響，以及艙室內的進水量和木材對破口處進水速度的影響，船舶總的進水速度、進水量、首尾吃水、穩性的實時狀態和最終船舶的總縱強度，給出了計算實例，並進行了在採取用泵抽水前後浮態參數的對比，得出了該船舶在艙室內的貨物積載量達到某個數值時可以保證船舶在破艙進水時不會沉沒，或者在當開口小於某數值時，採取適當的措施后，可以使船舶避免沉沒。
  2. After construction of the prior landmark models based on principal component analysis technique, structures of objects can be located by adjusting the model parameters in a learning way that it minimizes the distances of corresponding landmark points between model and object. a good overall match is obtained in a few iterations

    它首先運用主分量分析方法（ pca ）建立目標輪廓的先驗模型，而後通過學習的方法不斷調整模型參數來減少模型與目標輪廓的距離誤差，最終在多次迭代后達到模型與實際目標的匹配。
  3. 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） 。
  4. The method reduces the data to search via decomposing the image to several effectual subimages by the wavelet, then reduces the searching space through multi - resolution analysis, and refine the solution using an iterative refinement algorithm finally

    該方法利用小波變換將圖像分成若干層次，通過引入有效子圖的概念來降低待搜索的數據量，應用小波理論的多分辨分析思想來縮小搜索空間，最後通過迭代求精演算法實現了圖像的快速、高精度配準。
  5. Problem c and problem d are also dual. they have a dual property that there are at least three " critical points " corresponding to an optimal straight - line in problem c and there are at least three " critical straight - lines " corre - sponding to an optimal point in problem d. from these properties, these four non - linear prob - lems could be transformed into combinatorial problems and could be solved by algorithms with polynomial - time iterations

    問題c和問題d也是對偶問題。問題c和問題d也有很好的對偶性質：在問題c中，對應於一條最優直線，至少存在三個「臨界點」 ；在問題d中，對應於一個最優點，至少存在三條「臨界直線」 。基於這種性質，這四個非線性優化問題便轉化為組合問題，從而得到迭代次數為多項式的演算法。
  6. But, pso convergence ' s speed become slow in latter iterative phase, and pso is easy to fall into local optimization. at present, some scholars improve base pso mostly using 3 methods : disperse algorithm, increase convergence speed, enhance particle ' kinds. in the paper, i put forward 2 methods aiming at local best resutl but not whole best result. i modify base pso using the last method. some scholars put forward times initializations, so i select best result after circulating some times to be a parameter of formula. first, put particle into some small region, and ensure every region having one paticle at least. second, every region ' s particle has probability transfer other regions. although increase running time, enhance particle ' kinds, decrese the probability of convergence far from whole best result. nerms ( network educational resource management system ) is one of the research projects in the science and technology development planning of jilin province. the aim of nerms is to organize and manage various twelve kinds of network educational resources effectively so that people can share and gain them easily and efficiently, so as to quicken the development of network education

    但粒子群演算法仍存在如下不足:首先在多峰的情況下，粒子群有可能錯過全局最優解，遠離最優解的空間，最終得到局部最優解;其次在演算法收斂的情況下，由於所有的粒子都向最優解的方向群游，所有的粒子趨向同一，失去了粒子間解的多樣性，使得後期的收斂速度明顯變慢，同時演算法收斂到一定精度時，演算法無法繼續優化，本文對原始粒子群演算法提出了二點改進方案: 1 .演算法迭代到一定代數后，把此時找到的全局最優解當作速度更新公式的另一參數（本文稱之為階段最優解）再進行迭代; 2 .每次迭代過程中除最優解以外的每個粒子都有一定概率「變異」到一個步長以外的區域，其中「變異」的粒子在每一維上都隨機生成一個步長。
  7. Not only the categorization results coursed by email feature fields, the numbers of features and iteration are presented and discussed, but also the performance of hierarchy categorization and direct categorization is compared, so appropriate settings are done according to the empirical results

    本文將最大熵模型用於郵件分類中，比較了多種特徵組合方式、特徵數、迭代數、層次分類及直接分類的分類效果。根據實驗結果選擇合適的分類設置。
  8. 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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