算術練習 的英文怎麼說

中文拼音 [suànshùliànxí]
算術練習 英文
arithmetic exercises
  • 算 : Ⅰ動詞1 （計算數目） calculate; reckon; compute; figure 2 （計算進去） include; count 3 （謀劃;計...
  • 術 : 術名詞1. （技藝; 技術; 學術） art; skill; technique 2. （方法; 策略） method; tactics 3. （姓氏） a surname
  • 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...
  • 算術 : arithmetic figure; arithmetic
  • 練習 : 1. （反復學習） practise; practice 2. （習題或作業等） exercise
  1. 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。
  2. 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。
  3. Long range virtual laboratory means realizing all kinds of long range laboratory environment through virtual earthy technology. the custom can complete every experimental item in the virtual laboratory like in the real environment. the effect of learning and training in the virtual laboratory equals to or be better than that in the real environment

    遠程虛擬實驗室是指在計算機系統中採用虛擬現實技術實現的各種遠程實驗環境，實驗者可以象在本地真實環境中一樣完成各種預定的實驗項目，所取得的學習或訓練效果等價于甚至優于在真實環境中所取得的效果。
  4. Machine learning algorithm discussed in this paper is not the same of the traditional ones, the later needs training samples which include positive and negative ones however we only provide positive ones, i. e. no attack events, for intrusion detection machine learning algorithm during training phase

    文中所討論的在入侵檢測技術中應用的機器學習演算法，在訓練階段只有正例樣本，這是與其它機器學習演算法的不同之處。
  5. It has used to forecast the full - time teachers in higher educational institutions in zhejing province by grey model and the artificial neuron network. this paper has acquired the better calculation result based on the advanced bp algorithm

    文中運用人工神經網路的技術，採用改進自適應學習速率和動量項系數的bp演算法，對浙江省高等學校專任教師數進行有導師的訓練和預測。
  6. By means of the proposed reinforcement learning algorithm and modified genetic algorithm, neural network controller whose weights are optimized could generate time series small perturbation signals to convert chaotic oscillations of chaotic systems into desired regular ones. the computer simulations on controlling henon map and logistic chaotic system have demonstrated the capacity of the presented strategy by suppressing lower periodic orbits such as period - 1 and period - 2. meanwhile, the periodic control methodology is utilized, the higher periods such as period - 4 can also be successfully directed to expected periodic orbits

    該控制方法無需了解系統的動態特性和精確的數學模型，也不需監督學習所要求的訓練數據，通過增強學習訓練方式，採用改進遺傳演算法優化神經網路權系數，使之成為混沌控制器，便可產生控制混沌系統的時間序列小擾動信號，模擬實驗結果表明它不僅能有效鎮定混沌周期1 、 2等低周期軌道，而且在周期控制技術基礎上，也可成功將高周期混沌軌道（如周期4軌道）變成期望周期行為。
  7. We attempt to exploit various machine - learning techniques to learn the heuristic knowledge from users " experiences, so that the image segmentation system can have some human ability in adaptively selecting optimal algorithm and corresponding parameters. learning based image segmentation system can be classified i

    希望使用機器學習的技術，通過從用戶對訓練圖像集的分割和評價中學習相應的啟發式知識，以此使系統能夠根據圖像的特徵，為不同的圖像靈活的選擇參數或演算法，從而自動實現令人滿意的分割。
  8. This thesis expounds fundamental principle and realization technique of artificial neural network and genetic algorithm, and redacts artificial neural network procedures. - ( l ) adopting batch processing high - speed algorithm, the thesis redacts back - propagation network procedure to enchance training velocity, in which learning rate and momentum parameters are modulated self - adaptably during error correction

    本文闡述了人工神經網路和遺傳演算法的基本原理及實現技術，並在此基礎上利用matlab5 . 3編寫了人工神經網路程序： （ 1 ）編寫了bp人工神經網路程序，採用vogl 「批處理」快速演算法，學習速率、動量參數在誤差修正過程中自適應調節，提高了訓練的速度。
  9. Firstly, this paper analyses concepts, characteristics and logic development relation of agent, software agent and mobile agent. this paper pays more attention to key components of intelligent model of mobile agent and migration plan of mobile agent, training and learning of mobile agent, choice of host, migration strategy of mobile agent based on machine learning and correlation analysis. referring to masif and the exploitation of mobile agent platforms at present, this paper hammers at interlinking these platforms to realize true rem otion independent of them, which premises for manufacturing a mobile agent platform

    本文首先分析了agent 、軟體agent 、移動agent的概念、特性及其邏輯發展繼承關系，顯示出了移動agent計算模式在低帶寬、高延遲環境下的優勢，重點研究移動agent智能遷移模型、移動agent遷移計劃、 agent的學習與訓練、 host選擇、基於機器學習的移動agent遷移策略等有關移動agent的關鍵技術，參照互操作性的規范masif ，根據目前移動agent平臺開發情況，致力於把這些平臺互連起來實現agent真正的跨平臺移動，為研製開發移動agent平臺做前提性研究工作。
分享友人
分享到 Line

分享到臉書