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back-propagation network in Chinese

Pronunciation:
How to pronounce "back-propagation network""back-propagation network" in a sentence

Translationmobile phoneMobile

  • 倒傳遞網(wǎng)絡(luò)
  • 反傳網(wǎng)絡(luò)

Examples

  • Application of improved back - propagation network in the evaluation of railway rock slope
    網(wǎng)絡(luò)在巖質(zhì)邊坡穩(wěn)定性評(píng)判中的應(yīng)用
  • 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(gè)c程序包，說(shuō)明了一個(gè)分析日斑數(shù)據(jù)的網(wǎng)絡(luò)。
  • 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(kāi)發(fā)了系統(tǒng)的缺陷分類(lèi)方法,用bp神經(jīng)網(wǎng)絡(luò)構(gòu)建了系統(tǒng)的分類(lèi)器。
  • 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(jīng)元網(wǎng)絡(luò)設(shè)計(jì)理論，包括單神經(jīng)元控制的結(jié)構(gòu)和基本理論及bp神經(jīng)網(wǎng)絡(luò)設(shè)計(jì)； 4
  • 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(wǎng)絡(luò)是人工神經(jīng)網(wǎng)絡(luò)中前向網(wǎng)絡(luò)的核心內(nèi)容，它在函數(shù)逼近、模式識(shí)別、數(shù)據(jù)壓縮等方面使用非常廣泛。
  • 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(shè)計(jì)了用于雜草形狀識(shí)別的bp網(wǎng)絡(luò)，結(jié)構(gòu)為6 - 12 - 3 ，并對(duì)學(xué)習(xí)誤差、隱層結(jié)點(diǎn)數(shù)對(duì)網(wǎng)絡(luò)性能的影響進(jìn)行了研究。
  • Besides stability , bifurcation and chaos in neural networks have receiving much attention recently . in this dissertation , we propose two neuron models with chaotic dynamics , which constitute chaotic neural networks that encompassed various associative and back - propagation networks
    除了穩(wěn)定性之外，極限環(huán)以及混沌也是神經(jīng)網(wǎng)絡(luò)動(dòng)態(tài)行為研究的重點(diǎn)，本文構(gòu)造了具有混沌解的兩種神經(jīng)元模型，通過(guò)混沌神經(jīng)元的耦合可以構(gòu)成混沌神經(jīng)網(wǎng)絡(luò)。
  • ( 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(xiě)了遺傳神經(jīng)網(wǎng)絡(luò)ga - bp程序，采用二級(jí)遺傳算法與bp算法相結(jié)合，同時(shí)優(yōu)化網(wǎng)絡(luò)隱層節(jié)點(diǎn)數(shù)和權(quán)值、閾值，既克服了尋優(yōu)過(guò)程的盲目性，又避免陷入局部極小，提高了網(wǎng)絡(luò)的學(xué)習(xí)精度。
  • 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(jù)小波變鵬胞強(qiáng)的特征提取能力和人工神經(jīng)網(wǎng)絡(luò)經(jīng)訓(xùn)練后具有較強(qiáng)的分類(lèi)能力的特點(diǎn)，本文把多維小波與目前應(yīng)用廣泛的bp （ backpid剛on ）相結(jié)合釀成小波神經(jīng)網(wǎng)絡(luò)，并以表征故障的特征向量作為小波神經(jīng)網(wǎng)絡(luò)的輸入。
  • 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(jīng)網(wǎng)絡(luò)和遺傳算法的基本原理及實(shí)現(xiàn)技術(shù)，并在此基礎(chǔ)上利用matlab5 . 3編寫(xiě)了人工神經(jīng)網(wǎng)絡(luò)程序： ( 1 )編寫(xiě)了bp人工神經(jīng)網(wǎng)絡(luò)程序，采用vogl “批處理”快速算法，學(xué)習(xí)速率、動(dòng)量參數(shù)在誤差修正過(guò)程中自適應(yīng)調(diào)節(jié)，提高了訓(xùn)練的速度。
  • More examples：  1  2
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