back propagation network 中文意思是什麼

back propagation network 解釋
反傳網路
  • back : n 1 背，背部；背脊；背面，反面；背後，後部，後面，裏面。2 （指）甲；（刀）背；（手）背；（書）背...
  • propagation : 持續培養
  • 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. Application of back propagation neural network to confect high strength premixing pumping concrete

    神經網路在高強泵送混凝土配製中的應用研究
  2. Firstly, second harmonic component ratio and dead angles of two phase inrush ' s dispersion in three - phase transformes are acted as input variable. secondly, the method applies improved algorithm based on the original algorithm of multi - layer forward back propagation network, that is to say, adding last variational effect of weight value and bias value to this time and making use of variable learning rate. at the same time, this method also adopts dynamic form in the number of hidden floor node

    首先，文中將三相變壓器兩相涌流差流的二次諧波含量比和間斷角作為網路的輸入變量；其次，利用對原有bp網路訓練演算法基礎上的改進型演算法（即在計算本次權值和閾值的變化時增加上一次權值和閾值變化的影響以及採用變學習率，與此同時隱含層神經元個數採用動態形式） ，通過樣本訓練使網路結構模型達到最優。
  3. 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。
  4. A particularly interesting item is the back - propagation network, a c package that illustrates a net that analyzes sunspot data

    特別有趣，它是一個c程序包，說明了一個分析日斑數據的網路。
  5. In order to overcome problems arisen from the application of x fluorescence analysis into complex spectrum produced by archaeological ceramic fragments with multi - element, low content and thick ground, we have employed the artificial neural network into the research of x fluorescence archaeology and conducted three kinds of research works. as the first one, we have applied the linear olam network ( optimal linear association memory network ) and the non - linear bp network ( back - propagation network ) respectively to analyze the complex x fluorescence spectrum of archaeological samples, and taken both results of spectrum analysis to compare with each other. the second, the method of pattern recognition of bp network was tentatively used to perform intelligent identification of production places of these archaeological samples

    針對科技考古中對大量考古陶片進行產地研究時x熒光分析對多元素、低含量、厚基底考古陶片產生的復雜譜分析的問題，將人工神經網路引入x熒光考古中，進行了三方面的研究工作：一是用線性olam網路（最優線性聯想網路）和非線性bp網路（誤差反傳導網路）分別對考古樣品的x熒光復雜譜進行解譜，並比較二者的解譜效果；二是用bp網路模式識別方法對考古樣品的產地進行智能識別；三是為了提高網路運算的可靠性和減小基體效應及電噪聲的干擾和影響，研究並提出了三種網路學習前的譜數據預處理方法。
  6. Neural network method is applied to the strength prediction. the ratio of water to cement material, the mass of fly ash and the silicon fume are regarded as network inputs and th e 28d strength is the target. the inputs and target are used to train a three layers back - propagation network

    在神經網路應用中，以水膠比、膠凝材料用量和粉煤灰摻量作為輸入，以28d抗壓強度作為目標輸出，對一個三層bp網路進行了訓練，然後利用訓練后的網路對已知配比和28d抗壓強度的混凝土進行了強度預測。
  7. Taking the evaluation criterion of lake nutrient states as sample pattern, the network was trained in the light of learning rule of error back propagation network

    將湖泊營養狀態評價標準作為樣本模式提供給網路，按照誤差逆傳播網路的學習規則對網路進行訓練，經過39925次學習后，網路達到預先給定的收斂標準。
  8. In the final part of the paper, the feasibility of applying neural networks to evaluate the performance of the columns is investigated. a three - layer back - propagation network is trained using the earthquake - resistant behavior experimental data of the columns to predict the ductility of the columns. the predicted results agree well with the test results

    在論文的最後，探索應用人工神經網路對核心柱的力學性能進行評估的可能性，利用該柱抗震性能試驗的結果，訓練一個三層bp網路，進行了柱抗震延性的預報，預報值和試驗值吻合良好。
  9. Error back propagation network is one kind of ann and it ' s widely used in economics prediction

    誤差反向傳播網路（ ebp網路）是人工神經網路的一種，它被大量運用在經濟學的預測問題上。
  10. The design theory of neural networks is discussed, including the basis principles of neuron control and the design of back - propagation network. 4

    探討了面向控制的神經元網路設計理論，包括單神經元控制的結構和基本理論及bp神經網路設計； 4
  11. Thickness is an effective feature for identifying corn from monocotyledonous weed, and the correctness was 90 %. ( 6 ) six shape features were used to design back - propagation network for weed identification and the network structure was 6 - 12 - 3

    （ 6 ）設計了用於雜草形狀識別的bp網路，結構為6 - 12 - 3 ，並對學習誤差、隱層結點數對網路性能的影響進行了研究。
  12. In view of this, to maintain the information of the original data, the pga ( principal component anylysis ) method is applied to preprocess the input mode, which improves the generaziation performance of bp ( back propagation ) network by turning multi - dimension variable into four - dimension variable, and four principal components are take out containing 85. 345 % of the information of the original data

    鑒於此，論文採用了主成分分析法，在基本保持原有信息的情況下，化高維為四維，提取了可包含有原始數據信息的85 . 345的前四個主成分因子變量，並計算這四個主成分的因子得分。
  13. Then a dynamic analysis model based on bp ( back - propagation ) network was established in accordance with the complexity and time - consuming character of the dynamic analysis in the reliability simulation of elastic linkage mechanism

    針對進行可靠性數值模擬時求解機構動力響應過程的復雜性和耗時性，構建了基於bp網路的動力響應分析模型。
  14. Application of improved back - propagation network in the evaluation of railway rock slope

    網路在巖質邊坡穩定性評判中的應用
  15. Algorithms for defect classification are developed. classifiers are constructed based on back - propagation network. the network configuration bases on input and output

    2 .研究和開發了系統的缺陷分類方法，用bp神經網路構建了系統的分類器。
  16. The back - propagation network is the core part of ahead - propagation network in artificial neural network and is widely applied in many aspects such as function approach, mode distinguishing and data condensation

    Bp網路是人工神經網路中前向網路的核心內容，它在函數逼近、模式識別、數據壓縮等方面使用非常廣泛。
  17. ( 2 ) combining secondary genetic algorithm with back - propagation network, the thesis redacts genetic neural network procedure, which optimizes number of hidden node and weight value and threshold value simultaneously. the procedure overcomes blindness during search, avoids falling into localminimum and increases learning accuracy

    （ 2 ）編寫了遺傳神經網路ga - bp程序，採用二級遺傳演算法與bp演算法相結合，同時優化網路隱層節點數和權值、閾值，既克服了尋優過程的盲目性，又避免陷入局部極小，提高了網路的學習精度。
  18. Because wavelet transform has forceful ability to pick - up character and artificial neural network has a strong capability to classify information. in this paper, the wavelet network has been formed by the wavelet transform, which is multi - dimension wavelet, and the artificial neural network which is back - propagation network. taking the eigenvector as an input of the wavelet network, the wavelet network can fulfill diagnosis of faults

    根據小波變鵬胞強的特徵提取能力和人工神經網路經訓練后具有較強的分類能力的特點，本文把多維小波與目前應用廣泛的bp （ backpid剛on ）相結合釀成小波神經網路，並以表徵故障的特徵向量作為小波神經網路的輸入。
  19. 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。
  20. Genetic algorithm is used to optimize the initial weight of back propagation network and the operation efficiency is enhanced

    用遺傳演算法優化bp網路的初始權值，提高神經網路的運算速度。
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