back propagation algorithm 中文意思是什麼
back propagation algorithm
解釋
倒傳遞演- 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
- algorithm : n. 【數學】演算法；規則系統；演段。
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To achieve this goal, this paper design a neural network with three layers in which the first layer play a classifier role and learn with the memory - based learning algorithm while the second and third layers learn with the error back - propagation algorithm
根據這一需要，本文建立了三層神經網路，第一層起分類作用，採用基於記憶學習演算法，第二、三層採用誤差反饋學習演算法。 -
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。 -
Based on polymerization reaction of the nylon - 6 rubberized cord fabric production of distributed control system in yangzhou organic chemical plant computer integrated manufacturing system ( yh - cims / dcs ), the multiple stepwise regression method was used to build the statistic mathematical models of the molecule weight and the monomer quantum of casting slice belt. then the optimization model of polymerization reaction was presented, which was solved by using simulation annealing algorithm to obtain the best techniques parameters. the improved hybrid genetic algorithm and back propagation algorithm are combined to train neural network, brought out the neural network prediction model of casting slice belt ' s average molecule weight to guide the technologist on - line
提出了流程工業生產過程操作優化策略和應用實施方法，包括生產過程離線優化策略、非線性問題求解策略、在線優化模型及學習策略；結合揚州有機化工廠計算機集成製造系統集散控制系統（ yh - cims dcs ）的實施，針對錦綸? 6浸膠南京理工大學博士學位論文摘要簾于布生產中己內酚胺聚合反應過程優化控制這一工程實際問題，採用統計建模方法，建立了聚合反應過程的優化模型；為求解所得的優化模型，提出了種改進的有約束條件下的模擬退火演算法，該演算法能避免陷於局部最優解，有效地提高了所求解的全局性和可靠性：提出了基於改進的ga演算法和sp演算法相結合的混合學習演算法，建立了基於神經網路的聚合反應過程生產目標在線預測模型，該演算法和模型滿足了生產中的實時性和實用性要求。 -
This paper proposed some methods for finding out sure regions and ambiguous regions defined by lower and upper approximations in rough set theory. an applicable ending - criterion for semi - supervised back - propagation algorithm was proposed and a new rough classifier framework was studied, the assessment results show the effectiveness of the proposed criterion. a new classifier based on support vector machines was studied and applied
本文提出了幾種劃分樣本邊界區的方法:提出了一種應用於半監督bp演算法的實用結束判據，並根據粗糙集理論，研究了一種新的粗糙分類機制，取得良好的效果；應用支持向量機理論，構造分類器並劃分樣本邊界區；最後研究多個分類器集成的方法尋找樣本邊界區，同樣提高了暫態穩定評估的可靠性 -
Based on the historical space forecast data and corresponding actual data provided by a global semiconductor assembly and test company, the uncertainty of space planning was defined. during this analysis process, linear regression, grey prediction, neural network back propagation algorithm and confidence interval were applied, respectively, to define the uncertainty. compared with those methods, the confidence interval of historical space forecast error, calculated by mathematical statistics, was the reasonable method to define the space forecasting uncertainty
本文從半導體工廠長期生產能力計劃的頂層即廠房生產面積的計劃展開，對一跨國半導體封裝測試公司提供的廠房生產面積的長期歷史預測數據以及對應的真實數據進行分析，採用線性回歸，灰預測，神經網路bp演算法，基於數理統計的置信區間的求解等方法分別定義廠房生產面積預測的不確定度，經多種方法的比較得出，基於數理統計方法求解出的生產面積歷史預測誤差置信區間能直觀清楚地標定不確定度。 -
In order to override the well - known limitation of back propagation algorithm, such as local grade problem, we suggest genetic algorithm, a global optimization algorithm, to optimize the weights set. the different parts of this model were modularized and combined as a prediction system
通過對固定網路結構的權系值進行遺傳操作，優化網路的權系值組合，快速收斂到最優權系值組合，進而提高網路的分析預測效率和能力。 -
The back - propagation algorithm also rests on the idea of gradient descent, and so the only change in the analysis of weight modification concerns the difference between t and y
反向傳播演算法同樣來源於梯度降落原理，在權系數調整分析中的唯一不同是涉及到t （ p ， n ）與y （ p ， n ）的差分。 -
In the stage of training, nntcs applies labeled documents to ann for training, and the error back propagation algorithm ( bp ) is employed to adjust weights of the networks. after training, the final fixed weights are saved as knowledge of classification
在文本訓練的時候，利用標記好的訓練文檔集進行網路訓練，誤差反饋演算法對網路進行權值調整，得到固定的權值作為分類知識存儲。 -
After researching the application of artificial neural network to fault diagnosis of transformer, the back propagation algorithm is improved observably. inducting chaos dynamics principium to create chaos neural network back propagation algorithm and using the pretreatment of training sample, the emulation program show that this method is effective
本文深入研究了人工神經網路在變壓器故障診斷中的應用，對目前最常採用的bp演算法做出了較大改進，在原有演算法中引入混沌動力學原理構造了混沌神經網路bp演算法，並提出了訓練樣本集的預處理方法，在模擬訓練中取得了滿意的效果。 -
Chapter four details the basis of the modeling of the thesis - - error back propagation algorithm, or bp, which is the stress of the thesis
2005年4月末，金融機構個人貸款余額達到27043億元，比上年同期增長了57 % ，呈現了快速發展的態勢。 -
Design of on - line learning based error back propagation algorithm in simulation servo system
基於在線學習誤差反傳演算法的模擬伺服系統設計 -
Chapter 4 presents an error back propagation algorithm with quadratic momentum of the multilayer forward neural networks that will speed up the error convergence velocity
本文提出一種帶二次動量項的多層前向網路誤差反傳演算法，提高了神經網路的誤差收斂速度。 -
Feature extraction through 2 - order polynomial fit of the descending part of the response curve made possible a timesaving measurement process. the performances of two pattern recognition algorithms, namely principal component analysis ( pca ) and linear discriminant analysis ( lda ) in practical problems were discussed. artificial neural network ( ann ) was utilized with back - propagation algorithm ( bpa ), and the combination of pca / lda with ann improved the identification performance of the system
基於對模式識別系統的深入研究，提出了從響應階段數據提取特徵的方法，節省了測試所需時間；比較了主成分分析法（ principalcomponentanalysis ， pca ）與線性判別式法（ lineardiscriminantanalysis ， lda ）兩種模式識別方法在實際應用中的不同結果，分析了原因；設計了採用誤差反傳演算法back - propagationalgorithm ， bpa ）的前向人工神經網路（ artificialneuralnetwork ， ann ） ，並指出其應用中存在的問題，提出了改進建議；利用pca lda與ann相結合的方法改善了系統的識別性能。 -
5 based on studying artificial nerve network theory, establish the nerve network model of cutting parameter. use back propagation algorithm ( bp algorithm ) as system ' s nerve network learning method. system has realized cutting parameter nerve network intelligentized choosing function
5在深入研究人工神經網路理論的基礎上，建立了切削參數選擇的神經網路模型，採用誤差反傳演算法（即演算法）作為切削參數智能選擇的神經網路學習方法，實現了切削參數人工神經網路智能選擇功能。 -
The application of hybrid algorithm which combines improved genetic algorithm and error back - propagation algorithm in artificial neural network training is studied first
首先研究了將改進遺傳演算法和誤差反向傳播（ bp ）演算法相結合的混合演算法來訓練人工神經網路。 -
The living example certification indicates that the neural networks model of this paper possesses the good convergence with the error back - propagation algorithm, and can pledge the satisfactory mapping precision, and gain the forecasting result of ideal, and provides the reliable basis for the policy decision
實例驗證表明本文的神經網路模型用誤差反向傳播演算法具有良好的收斂性，能夠保證滿意的映射精度，取得了理想的預測結果，為決策提供了可靠的依據。 -
Based on gradient descent rule, the bp ( back propagation ) algorithm is a local optimization algorithm
Bp演算法基於梯度下降原理，是一種局部尋優演算法。 -
Using error back propagation algorithm. the limitation of the bp net is also improved ; 2 > when prediction with little training sample set and large variable size is concemed, this paper abstracts the prime factors from the training sample set using rough set theory, then only inputs the prime factors into ann. this diminishes the size and the input nodes number of ann
對于即網路本身易陷入局部極小點及收斂速度慢的問題，在文中也得到了改進； 2 、對于財政轉移支付中標準收入的測算屬于多指標小樣本的預測問題，文中首次利用粗集理論對初始的指標體系進行約簡，提取出關鍵性的因素作為神經網路的輸入。 -
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。 -
Bp ( back propagation ) algorithm is the most popular training algorithm in applications for its non - linear mapping approach capability and robustness. however, it has some defects, such as converging slowly and immersing in local vibration frequently
Bp演算法以其良好的非線性映射逼近能力和泛化能力以及易實現性成為人工神經網路應用最廣泛的訓練演算法，但是bp演算法也有其明顯的缺陷，即訓練速度慢、容易陷入局部極值等。
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