simulation of neural network 中文意思是什麼

simulation of neural network 解釋
神經網路模擬
  • simulation : n. 假裝；模擬；裝病，裝瘋；【生物學】擬態，擬色。
  • of : OF ＝Old French 古法語。
  • neural : adj. 【解剖學】神經（系統）的；神經中樞的；【解剖學】背的，背側的。adv. -ly
  • network : n. 1. 網眼織物。2. （鐵路、河道等的）網狀系統，網狀組織，廣播網，電視網，廣播[電視]聯播公司。3. 【無線電】網路，電路。4. 【計算機】電腦網路，網。
  1. Procreant knowledge expression and forward inference engine are adopted in the method of fault diagnosis based on expert system theory. in the fault diagnosis applying neural network theory, six kinds of improved arithmetic of back - propagation arithmetic, including gradient descent with momentum, variable learning rate back - propagation, resilient back - propagation, quasi - newton, levenberg - marquardt and conjugate gradient, are applied to diagnose the faults of electric load manage center and solid state power controller. different diagnostic results gotten by simulation are compared at last

    在基於專家系統的故障診斷方法中，採用了產生式知識表達和正向推理機制；在基於神經網路的故障診斷方法中，則分別採用了bp神經網路的附加動量法、自適應學習速率、彈性bp演算法、擬牛頓法、共軛梯度法和levenberg - marquardt法對電氣負載管理中心和固態功率控制器的故障進行診斷，並對由模擬得到的不同診斷結果進行比較。
  2. In this paper, wavelet neural network is used to extract the signal feature of three millimeter pulsed radar, and the simulation is done by the computer

    本文將小波神經網路用於三毫米脈沖體制雷達回波信號特徵的提取並做了計算機模擬。
  3. Through the simulation of large - scale circuit simulation proved that use the crossover tearing technology could detailed network structure, simplify the diagnostic process, and the neural network can parallel deal with the diagnosis information, and the logic operation can judge the information of the multi - fault. the illustrative simulation shows that it can increase the diagnosis speed and decrease the workload before test

    通過對大規模模擬電路的模擬證明，使用交叉撕裂明細網路結構，簡化診斷過程，且運用神經網路組對信息進行并行處理，邏輯分析運算對多故障信息進行處理判斷，大大提高了故障診斷速度，減小了測前工作量。
  4. Simulation of a neural network - based path planning algorithm for mobile robot

    基於神經網路的移動機器人路徑規劃演算法的模擬
  5. Simulation results show that both of them have satisfactory performance and strong robustness. 2. to ph processes, which are nonlinear and time varying, the neural network model is structured and the learning algorithm is presented, based on which the model - free controller is designed, while the controller gain is scheduled by a fuzzy method

    針對具有嚴重非線性和不確定性的ph中和過程，給出一種神經網路模型，提出了一種神經非模型控制方法，該方法利用模糊演算法在線調整神經網路控制器的增益，模擬實驗表明這種基於神經網路的非模型控制方法能有效控制ph過程，具有優良的控製品質和強魯棒性。
  6. 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。
  7. After analyzing the character of risk, i introduce data mining method into risk management, to solve the contradiction between great capacity of data and lack of information, the methods include mathematics statistics and artificial neural network ( ann ). then, i study on the methods of risk management in risk identification, risk evaluation and risk disposal, what is advanced, fault tree analysis method based on fuzzy probability, stochastic simulation method and the topsis method based on interval number all consider the characteristic of risk. finally, i discussed the application of information system ( mis ) in project risk management, and developed a risk management information system

    論文在深入分析了風險特徵之後，將數據挖掘技術引入風險管理，用以解決海量數據與貧乏信息之間的矛盾，所採用的技術有數理統計和人工神經網路（ ann ）兩種方法；接著，論文對風險識別、風險評價、風險處理中的風險管理方法進行了研究，所提出的基於模糊概率的故障樹技術、隨機模擬技術和基於區間數的topsis方法都體現了風險管理的特點；最後，論文對信息系統（ mis ）在工程項目風險管理中的應用進行了探討，開發出一個風險管理信息系統。
  8. In the algorithm level, currently various training algorithms of neural networks, including gradient algorithms, intelligent learning algorithms and hybrid algorithms, are comparatively studied ; the optimization principle of bp algorithm for neural networks training is analyzed in detail, and the reasons for serious disadvantages of bp algorithms are found out, moreover, the optimization principle of two kinds of improved bp algorithms is described in a uniform theoretic framework ; and the global optimization algorithms of neural networks, mainly genetic algorithm are expounded in detail, it follows that a improved genetic algorithm is proposed ; finally the training performances of various algorithms are compared based on a simulation experiment on a benchmark problem of neural network learning, furthermore, a viewpoint that genetic algorithm is subject to " curse of dimension " is proposed

    在演算法層，本文對目前用於神經網路訓練的各種演算法，包括梯度演算法、智能學習演算法和混合學習演算法進行了比較研究；對用於神經網路訓練的bp演算法的優化原理進行了詳細的理論分析，找到了bp演算法存在嚴重缺陷的原因，並對其兩類改進演算法-啟發式演算法和二次梯度演算法的優化原理，在統一的框架之下進行了詳盡的理論描述；對神經網路全局優化演算法主要是遺傳演算法進行了詳細的闡述，並在此基礎上，設計了一種性能改進的遺傳演算法；最後基於神經網路學習的benchmark問題對各種演算法在網路訓練中的應用性能進行了模擬研究，並提出了遺傳演算法受困於「維數災難」的觀點。
  9. The simulation results showed that the intelligent shift control could improve the powertrain efficiency of the engineering vehicle, and could overcome the low realtime behavior of neural network in the meantime

    模擬結果表明，該控制方法提高了工程車輛液力機械傳動系統效率，有效地克服了神經網路控制實時性差，難以在工程實際中應用的問題，實現了換擋控制的智能化。
  10. Research and simulation of neural network phase plane divisional control

    神經網路相平面分區控制器研究與模擬
  11. In the control scheme using neural network, the control of flexible manipulator is separated into angle - following control of slow subsystem and vibration - suppressing control of fast subsystem based on singular perturbation and time decomposition. moreover, the paper discusses the structure and the algorithm of neural network plus fuzzy pd control of tip vibration. finally the performance of designed methods is validated by simulation

    對于神經網路控制，首先根據奇異攝動和兩時標分解，將柔性連桿機械臂的控制分解成等效剛性臂慢子系統的角跟隨運動控制和快子系統的消振控制，論文給出了神經網路+末端振動模糊pd控制的結構和計演算法，並通過實驗研究驗證了提出設計方法的性能。
  12. The simulation results show the good performance for the system by using network to adjust the parameters and the recurrent weight of neural network on - line dynamically on the condition of variety of system parameter and the impact of outside uncertainty factors

    模擬結果表明，當系統參數動態變化或受到外部不確定因素影響時，利用神經網路來在線調整網路的隸屬函數參數以及神經網路遞歸權值，使系統具有良好的動靜態性能。
  13. Comparing the result of neural network forecast with that of numerical simulation, fracture time forecasted by the artificial neural network is precise and reliable

    最後將神經網路預測結果與數值計算結果對比，認為應用人工神經網路對立井井筒破裂時間的預測比較準確、實用。
  14. Based on compensation control thought, through using neural network pid controller as compensation tache of traditional pid controller, a kind of hybrid pid controller is designed. combined with neural network, self - tuning control can realized better control over non - linear system. utilizing the advantages of fuzzy control and neural network control, a kind of neural network adaptive fuzzy controller based on fast bp algorithm is presented and it may control the plant on line. at last, the hybrid pid controller is applied in tension system of h - section continuous rolling mills and tension - free control is realized. the simulation results show that it has better performance than traditional pid controller. at the same time, it provides some reference for the control of other similar systems

    在此基礎上，基於補償控制思想，利用神經pid對傳統pid進行補償，設計了一種混合pid控制器；神經網路與自校正控制的結合，使得自校正方法能對非線性系統實現比較理想的控制效果；利用模糊控制與神經網路控制各自的優點，提出了一種基於快速bp演算法的神經網路自適應模糊控制器，能夠對系統進行在線控制。最後將混合pid控制應用於h型鋼連軋機張力系統中，實現微張力控制，模擬結果說明其較傳統pid具有更好的性能，同時也為其它類似系統的控制提供一些參考。
  15. In this paper, the auv is the object of the research. in order to overcome the negative effects of the non - linear part of kinematic model, sea current and wave during motion control, a new type of neural network : fuzzy cerebellar model arithmetic controller ( fcmac ), together with an on - line learning scheme based on the lyapunov stability theory, has been adopted in designing the new motion control system. the simulation results have been compared with those generated by a classic pid controller

    本文以auv為對象，針對其運動控制中模型非線性部分對控制性能影響較大及有海流、海浪等外界干擾等特點，採用一種新型神經網路：模糊小腦模型關節控制器（ fuzzycerebellarmodelarithmeticcontroller ）並結合基於李雅普諾夫原理而推導出的學習演算法設計auv的運動控制系統，並與傳統pid控制器進行了模擬比較。
  16. In this thesis, a combined method of finite element numerical simulation with neural network is studied to obtain the dynamic response, the impetus forces and impact parameters of windshield during bird impact

    本文採用鳥撞實驗、有限元數值模擬與神經網路相結合的方法研究鳥撞飛機風擋過程中風擋的響應以及鳥撞實驗中撞擊力與撞擊參數的獲得。
  17. Application of neural network in calculation of aircraft ' s flight track simulation

    神經網路在飛行器航跡模擬計算中的應用
  18. Some methods, such as adding integrator ; making use of neural network to remember fuzzy rule ; utilizing bang - bang controller and adjusting scale and proportion factors online, are researched to modify normal fuzzy controller for optimizing srd ' s dynamic and static performance. the simulation results given in this paper show the srd with modified fuzzy controller has excellent performance

    本文以提高srd動、靜態性能為指標，研究了如下幾種改進模糊控制的方法： （ 1 ）串聯或並聯積分器以提高靜態精度； （ 2 ）利用神經網路記憶模糊控制規則； （ 3 ） bang - bang控制與模糊控制結合； （ 4 ）在線調整量化因子與比例因子。
  19. The more satisfactory result is obtained through simulating the star pattern recognition process on the simulation platform. the result indicates that it is feasible to make use of neural network technology to realize star pattern recognition, and it is easy to be realized

    經過在自行開發的星圖識別模擬平臺上模擬實現星圖識別的過程，得到比較滿意的結果，表明利用神經網路技術來實現星圖識別是可行的，且容易實現。
  20. The study of simulation of neural network fuzzy pid control method in the temperature control of greenhouse

    演算法在溫室溫度控制中的模擬研究
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