收斂程度 的英文怎麼說

中文拼音 [shōuliǎnchéngdù]
收斂程度 英文
degree 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; ...
  • 程 : 名詞1 （規章; 法式） rule; regulation 2 （進度; 程序） order; procedure 3 （路途; 一段路） journe...
  • 度 : 度動詞[書面語] （推測; 估計） surmise; estimate
  • 收斂 : 1 （減弱或消失） weaken or disappear 2 （約束言行） restrain oneself 3 [數學] convergence; constr...
  • 程度 : 1. （知識、能力的水平） level; degree 2. （事物變化達到的狀況） extent; degree
  1. The two - dimensional henon chaotic nonlinear map is effectively controlled by the proposed approach. secondly, because of the distinguished advantages, such as rapid convergency and strong approachability, the rbf networks is trained as chaotic controller by ogy scheme, then successful of controlling the henon chaotic map

    其次，利用一種學習過程收斂速度快、擬合能力強的rbf神經網路，以ogy法為依據，訓練網路成為混沌控制器，仍以henon映射作為混沌控制對象，對其混沌行為實施了成功控制。
  2. As soon as the servo system is concerned, the celerity of control algorithm is a very important capability guideline

    在計算機控制系統中，控製程序的時間間隔對控製品質有著很重要的影響，這就要求所設計的控制器收斂速度快。
  3. According to the low speed of constringency and high complexity of training methods in large scale training, particle swarm algorithm is brought forward to solve the problem

    針對在大規模訓練中演算法收斂速度慢、復雜程度高等問題，提出用粒子群演算法求解其中的二次規劃問題的思想。
  4. A lot of simulation results show that the sofia has the high convergency rate, accuracy and good stability. it can be conveniently applied to engineering practice

    大量的模擬結果表明該演算法具有收斂速度快、辨識精度高、穩定性好，便於工程應用。
  5. The method proposed in this thesis do well in solving the problems of multi - damping - ratio - spectra simulation. it is convenient to obtain the pareto optimal solution set of the multi - object question by using implicit parallel genetic algorithms and the method can meet the practical needs for simulating ground motions coinciding with multi - damping - ratio - spectra in seismic design. the crossing rate and variance rate are important parameters of genetic algorithms which affect the rate of convergence, the adapting rate of cross and variation in this paper can auto - adapt and according to stand or fall of current sample, it assures the sample approach to the pareto optimal solution set in fast convergent speed

    較好地解決多阻尼比反應譜擬合問題；本文方法通過一次運行就能獲得一組具有集系特性的地震動，在擬合多阻尼比反應譜的人造地震波集系的模擬方面有傳統方法所不能比擬的優勢，產生的人造波或人造波集系可滿足工程抗震設計需要；在遺傳演算法中，交叉概率和變異概率是影響收斂速度的重要參數，本文採用的改進自適應交叉概率和變異概率，可以根據當前樣本的好壞程度來自動地選擇適當的交叉概率和變異概率，以保證演算法始終以較好的速度向pareto最優解集逼近。
  6. This article puts forward a solution named divide - assemble by deducing the size of bp neural network to overcome entering the local best point, the dividing process is that a big bp neural network is divided into several small bp neural networks, every small bp neural network can study alone, after all small bp neural networks finish their study, we can assemble all these small bp neural networks into the quondam big bp neural networks ; on the basis of divide - assemble solution, this article discusses the preprocessing of input species and how to deduce the size of bp neural network further to make it easy to overcome entering the local best point ; for the study of every small bp neural network, this article adopts a solution named gdr - ga algorithm, which includes two algorithms. gdr ? a algorithm makes the merits of the two algorithms makeup each other to increase searching speed. finally, this article discusses the processing of atm band - width distribution dynamically

    本文從bp網的結構出發，以減小bp神經網路的規模為手段來克服陷入局部極小點，提出了bp神經網路的拆分組裝方法，即將一個大的bp網有機地拆分為幾個小的子bp網，每個子網的權值單獨訓練，訓練好以後，再將每個子網的單元和權值有機地組裝成原先的bp網，從理論和實驗上證明了該方法在解決局部極小值這一問題時是有效的；在拆分組裝方法基礎上，本文詳細闡述了輸入樣本的預處理過程，更進一步地減小了bp網路的規模，使子網的學習更加容易了；對于子網的學習，本文採用了最速梯度? ?遺傳混合演算法（即gdr ? ? ga演算法） ，使gdr演算法和ga演算法的優點互為補充，提高了收斂速度；最後本文闡述了用以上方法進行atm帶寬動態分配的過程。
  7. In chapter three, a back / forward sweeps based on branch loss for power flow is presents, which is credited with simple program, good numerical value stability, small ems memory and rapid calculation

    第三章介紹了基於支路網損的配電網前推回推潮流演算法，該演算法編程簡單，數值穩定性好，佔用內存小，計算速度快，並且收斂性和收斂速度均優于牛頓法。
  8. Neural network control is an important mode of intelligent control, and it is widely used in branches of control science, first, the architecture and the learning rule ( error back propagation algorithm ) of multiplayered neural network which is widely used in control system are presentedo especially, the paper refers to the architecture of diagonal recurrent neural network and its learning algorithm - - - - - recurrent prediction error algorithm because of its faster convergence with low computing costo next, before introducing the neural network control to the double close loop dc driver system, the controllers of current and velocity loop are designed using engineering design approach after analysis of the system, simulation models of the system are created

    神經網路控制是智能控制的重要方式之一，它廣泛應用於自動控制學科各個領域。本文首先敘述了控制系統中常用的多層前饋網路結構及演算法（ bp演算法） ，特別提及了能夠較好描述系統動態性能的對角遞歸神經網路和在用遞推預報誤差演算法訓練drnn時取得了較快的收斂速度。其次，應用工程方法分析設計了tf - 1350糖分離機的電流、轉速雙閉環直流調速系統的控制器，作為引入神經網路控制的設計基礎，並建立了系統的模擬模型。
  9. Compared with the classical bp algorithm, robust adaptive bp algorithm possesses some advantages as following : ( 1 ) increasing the accuracy of the network training by means of using both the relative and absolute residual to adjust the weight values ; ( 2 ) improve the robustness and the network convergence rate through combining with the robust statistic technique by way of judging the values of the samples " relative residual to establish the energy function so that can suppress the effect on network training because of the samples with high noise disturbances ; ( 3 ) prevent entrapping into the local minima area and obtain the global optimal result owing to setting the learning rate to be the function of the errors and the error gradients when network is trained. the learning rate of the weights update change with the error values of the network adaptively so that can easily get rid of the disadvantage of the classical bp algorithm that is liable to entrap into the local minima areas

    與基本bp演算法相比，本文提出的魯棒自適應bp演算法具有以下優點： （ 1 ）與魯棒統計技術相結合，通過訓練樣本相對偏差的大小，確定不同訓練樣本對能量函數的貢獻，來抑制含高噪聲干擾樣本對網路訓練的不良影響，從而增強訓練的魯棒性，提高網路訓練的收斂速度； （ 2 ）採用相對偏差和絕對偏差兩種偏差形式對權值進行調整，提高了網路的訓練精度； （ 3 ）在採用梯度下降演算法對權值進行調整的基礎上，通過將學習速率設為訓練誤差及誤差梯度的特殊函數，使學習速率依賴于網路訓練時誤差瞬時的變化而自適應的改變，從而可以克服基本bp演算法容易陷入局部極小區域的弊端，使訓練過程能夠很快的「跳出」局部極小區域而達到全局最優。
  10. To optimize the multi - phase homing trajectory, an improved adaptive genetic algorithm ( iaga ) was proposed, which could efficiently improve convergence speed and avoid the occurrence of premature

    在對分段歸航軌跡的優化中，提出了改進自適應遺傳演算法，該演算法通過增加「強化」運算元、改進對種群「早熟」程度評價指標等，有效地提高了收斂速度、避免了「早熟」現象。
  11. Finally, in the third section, by constructing some functional which similar to the conservation law of evolution equation and the technical estimates, we prove that in the inviscid limit the solution of generalized derivative ginzburg - landau equation ( ggl equation ) converges to the solution of derivative nonlinear schrodinger equation correspondently in one - dimension ; the existence of global smooth solution for a class of generalized derivative ginzburg - landau equation are proved in two - dimension, in some special case, we prove that the solution of ggl equation converges to the weak solution of derivative nonlinear schrodinger equation ; in general case, by using some integral identities of solution for generalized ginzburg - landau equations with inhomogeneous boundary condition and the estimates for the l ~ ( 2 ) norm on boundary of normal derivative and h ~ ( 1 ) ' norm of solution, we prove the existence of global weak solution of the inhomogeneous boundary value problem for generalized ginzburg - landau equations

    第三部分：在一維情形，我們考慮了一類帶導數項的ginzburg ? landau方程，通過構造一些類似於發展方程守恆律的泛函及巧妙的積分估計，證明了當粘性系數趨于零時， ginzburg ? landau方程的解逼近相應的帶導數項的schr （ ? ） dinger方程的解，並給出了最優收斂速度估計；在二維情形，我們證明了一類帶導數項的廣義ginzburg ? landau方程整體光滑解的存在性，以及在某種特殊情形下， gl方程的解趨近於相應的帶導數項的schr （ ? ） dinger方程的弱解；在一般情形下，我們討論了一類ginzburg ? landau方程的非齊次邊值問題，通過幾個積分恆等式，同時估計解的h ~ 1模及法向導數在邊界上的模，證明了整體弱解的存在性。
  12. Because the adaptive algorithm of conventional adaptive noise canceller is the least mean squares ( lms ), and the convergence rate of lms is heavily dependent on the eigenvalue distribution of the autocorrelation matrix of the input signal, thus lms converges at unacceptably low rates when the input signal is colored noise or speech

    由於傳統自適應噪聲抵消系統（ anc ）自適應演算法主要採用lms演算法，而lms演算法收斂速度依賴于輸入信號自相關矩陣特徵值的分散程度。因此，當輸入信號是語音或有色噪聲時， lms的收斂速度很慢。
  13. 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。
  14. This paper studies nonlinear dynamic problems of tall building structures, first, constitutes linear dynamic equation and elasto - plastic dynamic equation of structure by using qr method, later, solves the dynamic equation by using spline unconditional stable algorithm, last, programs corresponding computer programs with c program language, and calculates some example and a tall building in constructing the courses and the results prove that qr method is not only simple in calculating and fast in constringency rate, but also precise, that qr method is a effective and economic new method

    本文研究高層建築結構彈塑性動力問題，先利用qr法建立了結構線性動力方程及彈塑性動力方程，然後利用樣條無條件穩定演算法求解了動力方程，最後利用c語言編寫了相應的計算程序，計算了一些例題和分析了一個工程實例。 qr法在理論上及方法上不用有限元法及流動法則，避免了這些傳統方法在分析非線性問題時所帶來巨大困難的缺陷。計算結果表明，這種方法不僅計算簡便，而且精度高，收斂速度快，是一種經濟有效的新方法。
  15. The research methods of serpentine waveguide and groove guide have been introduced. eigen equation of rectangular groove guide is obtained by galerkin boundary integration equation method. more accurate results are got with four - order approximation, which show good convergence and better agreement with experimental data when compared with previously published papers

    利用galerkin積分方程法得到了矩形槽波導任意價精度下的本徵方程，計算得到1到4價精度下的本徵解，並且跟文獻中的試驗結果及其他方法得到的結果做了比較，結果顯示，本文的結果更接近於試驗數據，並且收斂速度快。
  16. This paper adopts multi - grid and the optimal selection of the relaxation gene, so it quickens the convergent speed of iteration

    方程組的求解過程中，採用了多重網格法的思想和優選法試驗鬆弛因子法，來加快迭代的收斂速度。
  17. An axial direction line multi - sensors placed method is presented. in the process of machine learning, use genetic algorithm to fit the curve of sensor ' s output. to improve the convergence speed of genetic algorithm, hill climbing method is joined with

    對示教過程中進行曲線擬和所用的遺傳演算法進行了一定的研究，為了解決遺傳演算法在接近收斂點時收斂速度慢的缺點，使用爬山法對其進行改進。
  18. Third, by means of smale, s point estimates theorem, the existence and the convergence theorem of broyden, s iteration is given, the method has less calculation and the speed of super linear convergence for solving the nonlinear equations with nondifferential terms under the point estimates or weak condition

    第三，本文利用smale提出的點估計理論，給出了在點估計和弱條件下，用計算量小、具有超線性收斂速度的broyden方法來求解帶不可微項的非線性方程，給出了存在性收斂性定理及相應的證明。
  19. Reinforcement learning algorithms that use cerebellar model articulation controller ( cmac ) are studied to estimate the optimal value function of markov decision processes ( mdps ) with continuous states and discrete actions. the state discretization for mdps using sarsa - learning algorithms based on cmac networks and direct gradient rules is analyzed. two new coding methods for cmac neural networks are proposed so that the learning efficiency of cmac - based direct gradient learning algorithms can be improved

    在求解離散行為空間markov決策過程（ mdp ）最優策略的增強學習演算法研究方面，研究了小腦模型關節控制器（ cmac ）在mdp行為值函數逼近中的應用，分析了基於cmac的直接梯度演算法對mdp狀態空間離散化的特點，研究了兩種改進的cmac編碼結構，即：非鄰接重疊編碼和變尺度編碼，以提高直接梯度學習演算法的收斂速度和泛化性能。
  20. The coupling analysis program of surface flow and subsurface flow over porous media is developed based on the conversion principles of water on the surface under rainfall conditions. a new method to judge the saturation of the surface is proposed in this thesis, the convergence is speeded up and the cpu time is saved by using this method

    根據非飽和土上水的轉化機理，編制了降雨條件下地表水入滲和產流耦合的計算程序，並根據土-水特徵曲線，提出了判斷地表飽和的條件，根據此條件，加速了收斂速度，節省了cpu的時間。
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