精練速度 的英文怎麼說

中文拼音 [jīngliànsùdù]
精練速度 英文
refining speed
  • 精 : Ⅰ形容詞1 （經過提煉或挑選的） refined; picked; choice 2 （完美;最好） perfect; excellent 3 （細）...
  • 練 : Ⅰ名詞1 （白絹） white silk 2 （姓氏） a surname Ⅱ動詞1 （加工處理生絲） treat soften and whiten s...
  • 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
  • 精練 : （使沒有多餘詞句） concise; succinct; terse; refining
  • 速度 : 1. [物理學] velocity; speed; blast; bat 2. [音樂] tempo3. （快慢的程度） speed; rate; pace; tempo
  1. The algorithm speeds up network study train, compared with the real - time recurrent learning algorithm consumedly, and increases the accuracy of prediction

    與已有的實時循環學習演算法相比，極大的提高了網路學習訓練的速度，並且提高了預測的精度。
  2. A new learning algorithm of the continue wavelet networks parameters is proposed, that is, hybrid parameters learning algorithm. the parameters of wavelet networks are divided into two parts, and different methods are used to training them. compare to the traditional parameters learning method, the new method proposed in this paper has the advantages of rapid convergence speed and high approximation capability

    提出了連續小波網路的混和參數訓練方法，將小波網路參數分為小波系數和網路權值兩部分，對這兩部分參數分別採用不同的方法進行訓練，這一新的訓練方法相對于傳統的小波網路參數訓練方法來說具有收斂速度快，逼近精度高等優點。
  3. 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。
  4. So when you get stale in your overall training routine, pick out one single " technique " and one single specific goal, i. e. " speed ", " power " or " accuracy "

    當你在訓練時提不起精神時，選擇一個單獨的「技術」或者一個單獨的目標，比如說， 「速度」 、 「力量」或「準確」 。
  5. Scrambling and motocross have had a long history in the new territories particularly with the british forces and expats stationed in hong kong. since moving to its new location in 1996 the hong kong mx club has grown from a single track to a large multi tracked park with many facilities. improved road access and increased popularity has seen the club membership grow

    Mx club會址在新界北區，擁有自己的會所及練習場地，還有提供專業訓練課程，推廣范圍包括有motocross速度越野trial技術幔爬越野atv四驅越野等，我地mx club定下決心做到熱心推廣培育精英的目標。
  6. Neural networks are used more frequently in lossy data coding than in general lossless data coding, because standard neural networks must be trained off - line and they are too slow to be practical. in this thesis, statistical language model based on maximum entropy and neural networks are discussed particularly. then, an arithmetic coding algorithm based on maximum entropy and neural networks are proposed in this thesis

    傳統的人工神經網路數據編碼演算法需要離線訓練且編碼速度慢，因此通常多用於專用有損編碼領域如聲音、圖像編碼等，在無損數據編碼領域應用較少，針對這種現狀，本文詳細地研究了最大熵統計語言模型和神經網路演算法各自的特點，在此基礎上提出了一種基於神經網路和最大熵原理的算術編碼方法，這是一種自適應的可在線學習的演算法，並具有精簡的網路結構。
  7. Observing the total error curve, the convergent speed is faster, and the error precision is higher then a group untrained experimental data are input the simulative system in turn. and their predicting results are satisfying

    根據小型催化裂化裝置進行重油催化裂化反應試驗的試驗數據對系統進行預測能力分析，從全局誤差曲線圖可見訓練速度比較快，誤差精度比較高。
  8. In this method, ga is used to optimize connection weights of forward - back neural network until the learning error has tended to stability, then we use sp algorithm with optimized weights to finish short - term load forecasting process

    我們用遺傳演算法來訓練網路參數，直到誤差趨於一穩定值，然後用優化的權值進行bp演算法，實現短期負荷預測，模擬實驗結果表明該方法加快網路學習速度，並能提高負荷預測精度。
  9. The simulation tests result indicates that the speed and precision of sample training are increased because of sample clustering for fuzzy modular networks. and the problem of slow training speed and local minimum point are avoided when bp networks are applied in the fault diagnosis of complex boiler

    本文所建的用於鍋爐故障診斷的模糊模塊化神經網路模型因進行了樣本聚類，實驗結果表明：其網路訓練的速度和精度明顯提高，同時有效地解決了bp網路應用於復雜的鍋爐系統故障診斷時，存在訓練收斂慢並容易陷入局部最小點的問題。
  10. In the training this network ' s topology structure and mapping function are the most optimal all along. and the learning velocity and precision are improved. with this recognition method shape pattern information and magnitude can be received rapidly and exactly, which can provide reliable data for later shape controlling

    本文將優化網路用於板形信號的模式識別，建立了6輸入、 3輸出的識別網路模型，該網路性能在訓練過程中始終保持最優，能夠達到最佳結構，加快了學習速度和訓練精度，可以快速、準確求出板形缺陷的模式信息及數值大小，為后續板形控制調節量的設定提供了可靠依據。
  11. According to request that military put forward, the target car that subject research should have such characteristics as remote control, high precision, good safeguarding, needing no track, etc, so as to achieve purpose of course require correctly when training to carry on cannon static to static, static to move, move to static, move to move etc. target car transfer speed require low inertia, high accuracy, high dependability, stupid and getting excellent and kind systematically ; wireless communication system expect much dependability, better anti - interference ability ; computer control system demand and try one ' s best to adopt advanced technology, components and parts source of goods reliable, high dependability, structure to be simple, have serial communication, digital display, systematic trouble examine and function of showing etc. the job of this thesis is divided into three major parts : the proposition and confirming of the electric power pulls, specification requirement and selecting type of equipment of communication system, sureness of the computer control system scheme

    根據軍方提出的要求，本課題研製的遙控坦克靶車應具有遙控、精度高、維護性好、無軌道、自帶動力等特點，以達到訓練時進行火炮或導彈靜對靜、靜對動、動對靜、動對動設擊等課目的要求。靶車調速系統要求低慣性、高精度、高可靠性、魯棒性好；無線通訊系統要求高可靠性、抗干擾能力強；微機控制系統要求盡量採用先進技術、元器件貨源可靠、高可靠性、結構盡量簡單，具有串列通訊、數字顯示、系統故障自檢及顯示等功能。本文的工作分為三大部分：電力拖動方案的提出及確定、對通訊系統的技術要求及設備選型、微機控制系統方案的確定。
  12. In training of back - propagation neural network, parameter adaptable method which can automatically adjust learning rate and inertia factor is employed in order to avoiding systemic error immersed in a local minimum and accelerating the network ' s convergence ; introduced the further optimization of the network ' s structure, it gives the research result of selection of the hidden layers, neurons, and the strategy of re - learning, compared the sums of the deviation square of this algorithm with conventional bp algorithm, as a result, the approach accuracy and the generalization ability of the network were extremely improved

    在對前饋神經網路的訓練中，使用參數自適應方法實現了學習率、慣性因子的自我調節，以避免系統誤差陷入局部最小，加快網路的收斂速度；提出了優化bp網路結構的實驗研究方法，並給出了有關隱含層數和節點數選擇以及再學習策略引進的研究結果。將該演算法同傳統bp演算法的預測偏差平方和進行比較，結果證實網路的逼近精度及泛化能力均得到了極大的提高和改善。
  13. During the process of constructing the model of analyzing customer churn, an improved algorithm is applied in this thesis directed toward drawbacks of computer network and thus raises the training accuracy and rapidity of convergence

    在客戶流失模型的構造過程中，本文針對神經網路演算法的缺陷運用了新的改進演算法，提高了訓練的精度和收斂速度。
  14. Furthermore, this paper exploringly studies an 802. 1 la high - speed wlan with the 54mbps data rate, and presents a sort of time synchronization and frequency offset estimation method based on the frequency domain auto - correlation of the unique preamble training sequence of 802. 11 plcp frame ; the method have the high time precision, the wide frequency estimat ion range and short convergence process ; and moreover, it can applied to other frame communication system

    另外本文還對最高傳輸速率為54mbps的802 . 11a高速無線局域網系統進行了探索性研究，討論了ofdm調制技術在無線局域網中的應用；結合802 . 11a物理層數據幀結構特點，提出了一種基於前導訓練符號序列的頻域自相關時間和頻率同步方法，此方法具有定時精度高、頻偏估計范圍寬和同步建立迅速等特點，也適合於其它幀通信應用場合。
  15. Besides, it is not fit with the precise adjustment and is difficult to conform the place. a new adaptive genetic algorithm with bp algorithm to optimize weight is backed up. the algorithm which combines the merits of the global convergence of genetic algorithm with fast local researching of bp algorithm not only intensifies the gradual convergence and evolution ability but also advance the speed of convergence, precision of training and generalization

    針對傳統遺傳演算法的搜索過程帶有一定的盲目性，其收斂特性不穩定且收斂速度緩慢，特別是在系統規模較大時，優化效果的明顯改善往往需要相當長的時間，而且不適合候選解的精調，難以確定解的確切位置，提出一種新型自適應性遺傳演算法，並在此基礎上，用bp演算法優化前向神經網路權值，綜合了兩種演算法的優點，即遺傳演算法的全局收斂性和bp演算法局部搜索的快速性，強化了遺傳演算法的漸進收斂和進化能力，全面改善了演算法的收斂性，提高了收斂速度及訓練精度，也擴展了泛化能力。
  16. Higher - order neural network of single _ layer has no trouble of hiding layer node, so training speed is fast ; ability of pattern classified increases ; the classification accuracy of pattern is improved without local optimality problem ; hierarchy can make training speed of each node neural network, and improve the classified accuracy of pattern

    單層高階神經網路沒有隱含層節點的困擾，訓練速度更快；模式分類能力更為強大；不存在局部最小的問題，模式分類精度更高；模式的不變性構建於網路結構之中等優點。分層方法能加快各節點神經網路的學習速度，也能提高模式劃分精度。
  17. In parameter analysis predict module includes the normalization method and principal component analysis, etc. make the neural network training efficiency and improve the speed

    在參數分析預測模塊包中對參數進行了歸一化及主元分析等項預處理，使神經網路的訓練效率及預測結果的速度、穩定性和精度得到了提高。
  18. In this thesis, the ann is designed to a failure sorter which is used to detect the failure of control surfaces in order to get the losing status of each control surface and improve the rapidity and precision of the control surface failure detection. here, it is a control law robust, learning kinds of faults peculiarity, adopting in - out data to training net. causing training, we can raise its precision and speed

    本文將神經網路作為一個控制器用於故障狀態下的控制律重構，通過神經網路學習各種故障狀態的非線性特性，同時實時採集系統運行時的輸入輸出值作為訓練數據進行訓練，以此來提高重構的速度和精度。
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