收入速度 的英文怎麼說

中文拼音 [shōurùsùdù]
收入速度 英文
income velocity
  • 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...
  • 入 : Ⅰ動詞1 （進來或進去） enter 2 （參加） join; be admitted into; become a member of 3 （合乎） conf...
  • 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...
  • 度 : 度動詞[書面語] （推測; 估計） surmise; estimate
  • 收入 : 1 （收進來的錢） income; revenue; receipts; gainings; earning; gross; proceeds; takings 2 （收進...
  • 速度 : 1. [物理學] velocity; speed; blast; bat 2. [音樂] tempo3. （快慢的程度） speed; rate; pace; tempo
  1. People put forward radial basis function networks considering the conventional bp algorithm problems of slow convergence speed and easily getting into local dinky value

    對于傳統bp演算法存在的收斂速度慢和易陷入局部極小值問題，人們提出了徑向基函數網路。
  2. Introduction of prepotency operator in the initialize population step and the improved mutation operator accelerate the convergence process, and the introduction of new operator in forming new population step avoid converging in local optimum, and promote the ability of global convergence

    演算法在初始化種群階段引入了「優生」運算元，以及改進的變異操作使演算法的收斂速度大大提高；在形成新種群階段引入新的運算元避免了局部早熟，提高了全局收斂能力。
  3. 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。
  4. Instruction detection technology is core in instruction detection system, it include abnormity instruction and abused instruction detection, on the basis of traditional network security model, ppdr model, instruction detection principle and instruction technology analysis, the author has brought forward instruction detection method based genetic neural networks, adopted genetic algometry and bp neural networks union method, and applied in instruction detection system, solve traditional bp algometry lie in absence about constringency rate slowly and immersion minim value

    入侵檢測分析技術是入侵檢測系統的核心，主要分為異常入侵檢測和誤用入侵檢測。作者在對傳統網路安全模型、 ppdr模型、入侵檢測原理以及常用入侵檢測技術進行比較分析的基礎上，提出了一個基於遺傳神經網路的入侵檢測方法，採用遺傳演算法和bp神經網路相結合的方法?遺傳神經網路應用於入侵檢測系統中，解決了傳統的bp演算法的收斂速度慢、易陷入局部最小點的問題。
  5. 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。
  6. The main characteristics and advantages are : on one hand, we adopted the low - complexity bussgang algorithm, and did blind estimation to ofdm sub - channel according to the mean square error criterion ( mse ) and peak distortion criterion ; on the other hand, we used the differential detection, which accelerates the convergence speed and avoid the error transmission problem resulted from the bussgang algorithm

    這兩種演算法一方面採用了低復雜度的bussgang自適應演算法，分別依據均方誤差準則和峰值失真準則對ofdm系統子通道進行盲估計；另一方面通過引入差分檢測技術，加快了演算法收斂速度，克服了bussgang演算法帶來的誤差傳播問題。
  7. 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。
  8. 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。
  9. Then, an improved genetic algorithm is proposed to solve this problem. this algorithm makes trees with the source and all destinations are the space of operation and filter operation. with hybrid selection operator, competition among brothers, greedy operation, filter operation

    然後給出了一種基於遺傳演算法的實時多播路由選擇方法，並用改進的遺傳演算法進行了求解，該演算法採用包含源節點和目的節點的樹作為交叉和變異的空間的方法，通過加入混合選擇、小范圍競爭擇優的交叉變異操作，提高了全局搜索能力和收斂速度。
  10. 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。
  11. Because ga possesses the traits of can global random search, the robustness is strong, been use briefly and broadly, it didn ’ t use path search, and use probability search, didn ’ t care inherence rule of problem itself, can search the global optimum points effectively and rapidly in great vector space of complicated, many peak values, cannot differentiable. so it can offset the shortages of nn study algorithm, can reduce the possibility that the minimum value get into local greatly, the speed of convergence can improve, interpolation time shorten greatly, the quantity of training reduce

    因為遺傳演算法具有全局隨機搜索能力，魯棒性強、使用簡單和廣泛的特點，它不採用路徑搜索，而採用概率搜索，不用關心問題本身的內在規律，能夠在復雜的、多峰值的、不可微的大矢量空間中迅速有效地尋找到全局最優解，所以可以彌補神經網路學習演算法的不足，使陷入局部最小值的可能性大大減少，使得收斂速度提高，訓練量減小。
  12. Abstract : the design problem of reduced - order state observer for a class of multi - input multi - output ( mimo ) nonlinear time - varying systems is studied in this paper. a new design method of nonlinear reduced - order state observer is proposed, and the exponential convergence is proved for the proposed state observer. the observer has the characteristics of that the speed of convergence is adjustable. finally, an example is given to show that this approach is effective

    文摘:研究一類多輸入多輸出（ mimo ）非線性時變系統的降維狀態觀測器設計問題.提出一種非線性降維狀態觀測器設計方案，並從理論上證明了狀態觀測誤差的指數收斂性.其中設計的降維狀態觀測器具有收斂速度可調的特性.最後給出了數值算例，模擬結果表明了本文方法的有效性
  13. Simple genetic algorithm gets local minimization too easily and converges slowly. to solve these problems, adaptive crossover rate that has reverse hyperbolic rel ation with the numbers of iteration is designed, and adaptive mutation rate that has reverse proportion to the distances of parents and reverse exponential relat ion to the numbers of iteration is put forward. the practical simulation results show that the adaptive ga has greater convergence speed and larger probability o f getting the best solution

    簡單遺傳演算法存在著收斂速度慢、易陷入局部極小等缺陷.針對這些缺陷，本文設計出隨相對遺傳代數呈雙曲線下降的自適應交換率，並提出與父串間的相對歐氏距離成反比、隨相對遺傳代數指數下降的自適應變異率.實例驗證表明，具有自適應交換率和變異率的遺傳演算法在收斂速度和獲得全局最優解的概率兩個方面都有很大的提高
  14. The artificial neural net ( ann ) way is universal regard as one of the most effective ways of stlf. in this paper, some research is developed for stlf using ann ways in several parts : the first part is about the arithmetic of ann based on bp model, namely the advanced of traditional bp arithmetic, one alterable step and scale bp arithmetic based on comparability of model and probability of accepting bp arithmetic is used to enhances a lot the convergence rate of learning process of bp network, but also avoid the stagnation problem to some extent. it indicates that the ann ' s efficiency and precision by the way can be ameliorated by the simulation of real data

    神經網路方法在短期預測中已經被公認為較有效的方法，本文針對神經網路用於電力系統短期負荷預測的幾個方面展開研究工作：第一部分研究一般用於負荷預測的神經網路bp模型的演算法，即對傳統的bp演算法的改進，將一種基於模式逼近度和接受概率的變步長快速bp演算法應用到短期負荷預測，模擬結果表明該方法有效的改善了bp演算法收斂速度慢以及容易陷入局部最小點的缺點，從而提高了神經網路用於負荷預測的效率和精度。
  15. 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。
  16. The number of the hidden layers of mul - tilayer perceptrons ( mlps ) is analyzed, and three - layer perceptrons neural network is adopted ; by analyzing the mechanism of the neural cells in hidden layer, a method for combining genetic algorithm and bp algorithm to optimize the design of the neural networks is presented, and it solves the defects of getting into infinitesimal locally and low convergence efficiently, it can also solve the problem that it can usually obtain nearly global optimization solution within shorter time through using genetic algorithm method lonely ; several examples validate that this algorithm can simplify the neural networks effectively, and it makes the neural networks solve the practical problem of fault diagnosis more effectively

    對多層感知器隱層數進行了分析，確定採用三層感知器神經網路;通過對隱層神經元作用機理的分析，引入了遺傳演算法與bp演算法相結合以優化設計神經網路的方法，有效地解決了bp演算法收斂速度慢和易陷入局部極小的弱點，還可以解決單獨利用遺傳演算法往往只能在短時間內尋找到接近全局最優的近優解的問題;通過實例驗證了這種演算法能夠有效地簡化神經網路，使神經網路更加有效地解決實際的故障診斷問題。
  17. The following algorithms have been proposed and tested in the thesis : 1 frequency selective fading : combine the isomorphism between the input space and the output space and propose a new approach to blind equalization of the channel. compared with conventional methods, the new approach offers lower computational complexity, better performance, and more robust against the over - determination of the system order ; 2 time selective fading : a new approach to the equalization of time selective channel based on the zero - forced equalizer is proposed which is more simple in its structure of algorithm ; 3 time - varying channel : using the instantaneous mean value changes of the output signal to extract the information of channel variations and model it using ar model, kalman filter is then employed to track channel variations, it bears faster ability in tracking the variation of tv channels ; based on the isomorphism between the inputs and the outputs and some of the approaches using in mimo system, a new algorithm of equalization of simo time - varying channel is proposed, which also share the merits of being robust against the over - determination of the system order ; model the time - varying channel using the multi - resolution decomposition wavelets, and then a blind identification method based " on the model is proposed ; at last, a new model for equalization and identification of mimo system is proposed

    主要工作在以下幾個方面： 1 、針對頻率選擇性衰落通道：結合輸入輸出空間同構關系提出一種新的頻率選擇性通道均衡方法，與傳統方法相比，該方法計算量更小，收斂速度更快，性能更優，且對系統階次的過確定表現穩健，具有實際均衡應用價值； 2 、針對時間選擇性衰落通道：提出一種基於迫零均衡的時間選擇性通道均衡方法，演算法結構簡單； 3 、針對時變色散通道：利用瞬態均值曲線提取通道時變信息，對之ar建模，利用卡爾曼濾波器跟蹤時變通道抽頭變化，可以快速跟蹤通道變化；基於輸入輸出空間之間的同構關系以及多輸入多輸出系統的處理方法，提出了新的單輸入多輸出色散時變通道均衡與識別演算法，同樣具有對通道階次過確定保持穩健的優點；結合小波多解析度分析提出一種基於小波模型的通道盲識別演算法；研究時變的多輸入多輸出系統的盲均衡與盲反卷積問題，給出一種時變系統處理模型。
  18. Based on x - filtered lms algorithm and - filtered lms algorithm adaptive inverse control, we use a new variable step size lms algorithm. adding little computation, variable step size lms algorithm can result in fast convergence speed and low residual error simultaneously. the adaptive feedback control can counteract the beginning error of the system

    在原來的x -濾波lms演算法自適應逆控制和-濾波lms演算法自適應逆控制方法的基礎上，引入了新的變步長lms演算法，在計算量增加不多的前提下，能同時獲得較快的收斂速度和較小的穩態誤差；引入自適應的反饋補償控制克服了被控系統的直流零頻漂移，使控制系統在初開始工作階段快速收斂；還引入自適應擾動消除器，它能最大限度的消除擾動。
  19. To quicken convergence and improve model precision, a new algorithm is presented in this paper, which utilize construct orderliness property of self - organization feature maps ( sofm ), divide system input space and adopt 1 order or 2 order local model in each subspace individually instead of a global model

    為了提高收斂速度和模型精度，本文利用自組織映射網路拓撲有序特性，對系統輸入空間進行分割，在子空間中採用多個局部一階線性模型或二階模型代替全局模型的局部化方法。
  20. Through chaos optimization method embedded into the genetic algorithm. the algorithm with the combination the advantages of the genetic algorithm and chaos optimization method which need not the optimal problem function ' s differential and promote the ability of the genetic algorithm ' s locally meticulous search can be obtained with the faster convergence and the greater probability for the global solution. a chaotic sequence is inserted into the search procedure of genetic algorithm, which can overcome premature of the search by genetic algorithm and the speed of convergence is faster than standard genetic algorithm

    對遺傳演算法進行了理論分析，並且研究了遺傳演算法的設計與實現；利用混沌優化方法不依賴于梯度信息的性質，將其與遺傳演算法相結合，提出了一種求解連續不可微函數優化問題的混合遺傳演算法；基於對于符號動力系統的研究，利用混沌序列的遍歷性，將混沌序列引入遺傳演算法中，提出一種嵌入哈爾濱工程大學博土學位論文一混飩序列的遺傳演算法，該演算法有效地克服了標準遺傳演算法中的早熟現象，並且具有更快的收斂速度。 」
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