feedforward network 中文意思是什麼

feedforward network 解釋
前饋網路
  • feedforward : 前饋的
  • 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. The other is an improved fuzzy neural network that is joined a compensative operation layer and adopts the improved center - or - gravity defuzzication in feedforward fuzzy neural network based on gaussian fuzzy logical system

    其二是改進的補償模糊神經網路。該網路在基於高斯模糊邏輯系統的前饋模糊神經網路中加入了補償運算層和採用了改進型中心反模糊化器。
  2. Feedforward neural network based on bp algorithm constructs identification of plant and inverse controller

    我們採用基於bp演算法的前饋神經網路構造對象辨識器和逆控制器。
  3. The attenuation indexes of vertical direction components and level radial components of blast earthquake wave in the condition of far range are all larger than the one in the condition of close range. based on upwards analysises, relevant control ways and safety defending technology of blast vibration are given from the aspects of blast equipments, blast parameters, landform physiognomy, blast methods. and taking the practical data from blast scene as the sample, the blast shockproofness are forecasted by the feedforward nerve network model based on the prior knowledge of blast shockproofness, the regress analysis method and experience formula method, which supply the technology gist for

    並且，以爆破現場的實測數據為樣本，採用基於爆破震動強度先驗知識的前饋網路神經模型、回歸分析法及經驗公式法分別對爆破震動強度進行了預測研究，為爆破施工參數的確定提供了技術依據，確保整個爆破工程順利安全進行，並對這三種方法的預測結果進行了對比分析;對比分析表明，三種預測方法計算出來的結果精度相差甚大，從檢驗樣本值與預測結果值之間的相對誤差可以看出，人工神經網路法預測的結果較其他方法更接近於實際值，回歸分析預測法的精度又要高於經驗公式預測法。
  4. To make neural network more robust, a novel robust estimation function is proposed to improve the feedforward neural network according to the theorem of statistics

    為使神經網路更加穩健，本文根據統計學原理，在前饋神經網路基礎上，採取穩健估計方法改進神經網路。
  5. This paper describes a three - layer feedforward rough neural network which has four input rough neurons and ten input conventional neurons, five hidden rough neurons and one output rough neuron

    本文給出了三層前向粗神經網路，輸入層由4個粗神經元和10個一般神經元組成，隱層和輸出層分別由5個、 1個粗神經元組成。
  6. A new model about measuring harmonics on - line is proposed in this paper. after band pass filtering, sampling storage and the monitoring on - line with artificial neural network ( ann ), we can obtain the harmonics signal, which is used to compensate harmonics. using the basic principle of analog parallel harmonics measurement and a special multi - layer feedforward neural network, a corresponding harmonics measurement on - line is built

    在本文中提出了一種新型電網諧波監測系統模型，通過帶通濾波器，采樣存儲器以及神經網路組成的監測系統可以實時監測電網諧波，當電網中的3次、 5次、 7次諧波超過容許值時，給出控制信號啟動以記錄儀記錄諧波，並可以控制諧波補償，最終達到監督電網，抑制諧波、減小諧波的目的。
  7. Neural network stc has the capacity of restrain the disturbance on the feedforward loop and essentially is applied to the controlled object that probably disturbed by the environment

    神經網路自校正控制主要用於被控對象含有擾動的場合，這種控制對于抑制前饋通道中的干擾有極大的優越性。
  8. Three types of artificial neural networks, namely radial basis function network, feedforward network, stochastic network, and their application in the analysis of electromagnetic stop band structure in coplanar waveguide have been discussed

    本文研究了以下三種人工神經網路：徑向基函數網路、前向網路、隨機網路，並用於分析共面波導中的電磁阻帶結構。
  9. The multi - layer feedforward back - propagation neural network has found a widely expanding range of applications

    Bp網路是當前應用最廣泛的一種人工神經網路。
  10. Feedforward networks use back propagation algorithm to train a multi - layer network. after training, the multi - layer network can fit the function in the data space very well

    前向網路利用反向傳播演算法訓練多層網路，使訓練后的網路較好地擬合樣本空間中各點的函數值。
  11. Nonlinear dynamic modelling of sensors is an important aspect in the field of instrument technique. the recursive neural network is proposed for nonlinear dynamic modelling of sensors, as its architecture is determined only by the number of nodes in the input, hidden and output layers. with the feedback behavior, the recursive neural network can catch up with the dynamic response of the system. the recursive neural network which involves dynamic elements and feedback connections has important capabilities that are not found in feedforward networks, such as the ability to store information for later use and higher predicting precision. a recursive prediction error algorithm which converges fast is applied to training the recursive neural network. experimental results show that the performance of the recursive neural network model conforms to the sensor to be modeled, and the method is not only effective but of high precision

    根據動態校準實驗結果建立傳感器的動態數學模型，以研究傳感器的動態性能，是動態測試的一個重要內容.討論了遞歸神經網路模型在傳感器動態建模中的應用，給出了遞歸神經網路模型的結構及相應的訓練演算法.由於其反饋特徵，使得遞歸神經網路模型能獲取系統的動態響應.該方法特別適用於傳感器非線性動態建模，而且避免了傳感器模型階次的選擇的困難.試驗結果表明，應用遞歸神經網路對傳感器進行動態建模是一種行之有效的方法
  12. The paper makes research into the multiplayer feedforward networks and dynamic recursive networks, and proposes a method to estimate the speed and rotor flux of induction motors using the dynamic recursive networks. to the used dynamic recursive network model, the off - line dynamic bp algorithm has been reasoned out so as to observe induction motor state variables

    本文分別對多層前向網路和動態遞歸網路進行了研究，提出基於動態遞歸網路的異步電機的轉速估計和磁鏈觀測，針對採用的動態神經網路模型，推導了離線動態bp演算法，以便利用動態遞歸網路進行狀態觀測。
  13. To overcome the common problems, difficulty of determining the optimal structure and slow training process, present in bp neural network, a novel non - iterative training algorithm for multilayer feedforward neural network has been proposed

    為彌補與克服推斷測量的常用技術之一的神經網路中存在的隱節點難以11摘要確定和訓練速度慢問題，提出了一種可用於多層前向神經網路模型的非迭代快速訓練演算法。
  14. Feedforward fuzzy neural network is the result of organically integrating fuzzy technology and feedforward neural network

    前饋模糊神經網路是模糊技術與多層前饋神經網路有機結合的產物。
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