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multilayer perceptron中文是什么意思

  • 多層感知器

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  • 例句與用法
  • Approach to rule extraction and generation using rough multilayer perceptron networks
    網(wǎng)絡(luò)的規(guī)則提取及生成方法研究
  • The microsoft neural network algorithm creates classification and regression mining models by constructing a multilayer perceptron network of neurons
    microsoft神經(jīng)網(wǎng)絡(luò)算法通過構(gòu)建多層感知器網(wǎng)絡(luò)來創(chuàng)建分類和回歸挖掘模型。
  • Based on analyzing the multilayer perceptron neural network, it induces the error backpropagation algorithm while taking the hyperboloid tangential function as nonlinear activation function
    在分析多層感知器神經(jīng)網(wǎng)絡(luò)的基礎(chǔ)上,推導(dǎo)了雙曲正切函數(shù)為激勵函數(shù)的誤差后向傳播算法。
  • The microsoft neural network algorithm creates classification and regression mining models by constructing a multilayer perceptron network of neurons, providing support for nonlinear models that are too complex to derive by using other algorithms
    microsoft神經(jīng)網(wǎng)絡(luò)算法通過構(gòu)造神經(jīng)元的多層感知器網(wǎng)絡(luò)來創(chuàng)建分類和回歸挖掘模型,同時(shí)為過于復(fù)雜而無法使用其他算法派生的非線性模型提供支持。
  • For short-time natural gas load forecasting . based on analyzing tech situation at home and abroad, considering all kinds of factors which will have influence on load changes, a hybrid approach combined the self-organizing feature map ( sofm ) neural network with multilayer perceptron ( mlp ) is presented, and short-time load forecasting model is established
    針對大然氣短期負(fù)荷預(yù)測的問題,在分析了國內(nèi)外技術(shù)現(xiàn)狀的基礎(chǔ)上,綜合考慮影響負(fù)荷變化的各種因素,提出了基于白織織競爭網(wǎng)絡(luò)和多層感知機(jī)網(wǎng)絡(luò)棍合的大然氣短期負(fù)荷預(yù)測方法。
  • For the planar gap and the tridimensional vertical bend of shielded cpw, fdtd simulations are carried out to produce training and testing samples and error-back propagation algorithm is used to train the multilayer perceptron neural networks ( mlpnns ) . rapid and accuracy cad models of these structures are successfully obtained for the first time
    對于屏蔽cpw的間隙不連續(xù)性和垂直互連不連續(xù)性結(jié)構(gòu),采用fdtd方法獲取訓(xùn)練和檢測樣本數(shù)據(jù),用回傳算法訓(xùn)練多層感知器,首次成功地獲得了這些結(jié)構(gòu)快速、準(zhǔn)確的cad模型。
  • Two distinct bp training algorithms on multilayer perceptron type neural-network are developed to improve the trained network's quickness, robustness and generality . they are brought out from the combination of existing investigations-dynamic learning rate, momentum terms and quadratic function of weights, and amendment of desired error function respectively . the simulative results of rotating machinery fault pattern classification illustrated the effectiveness of the new algorithms
    針對多層感知器神經(jīng)網(wǎng)絡(luò)的標(biāo)準(zhǔn)bp訓(xùn)練算法存在推廣能力差和訓(xùn)練速度慢等缺陷,首先結(jié)合已有的研究成果,給出了一種動態(tài)學(xué)習(xí)率和動量項(xiàng)相結(jié)合,并在誤差函數(shù)中引入網(wǎng)絡(luò)權(quán)值的二次型函數(shù)項(xiàng)的改進(jìn)訓(xùn)練算法,提高了網(wǎng)絡(luò)的快速性和推廣能力。
  • If we concatenate the recognition results of each sensors and consider it as a joint feature vector of target, then decision level fusion for target recognition can be considered as a conventional pattern recognition problem . this dissertation uses multilayer perceptron to classify the joint feature vector
    將各傳感器輸出的識別結(jié)果連接起來作為目標(biāo)的一個聯(lián)合特征矢量,則決策層融合目標(biāo)識別可看作是一個常規(guī)的模式識別問題,本文采用多層感知器網(wǎng)絡(luò)對這個聯(lián)合特征矢量進(jìn)行分類,實(shí)現(xiàn)決策層融合目標(biāo)識別。
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