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initial weight in Chinese

Pronunciation:
How to pronounce "initial weight""initial weight" in a sentence

Translationmobile phoneMobile

  • 初始重量
  • 初重
  • 始重

Examples

  • Application of k - l transformation the optimization of initial weights of bp neural network
    網(wǎng)絡(luò)初始權(quán)值優(yōu)化中的應(yīng)用
  • Nntcs employs genetic algorithm ( ga ) in the stage of training to optimize initial weights of ann
    訓(xùn)練過程中結(jié)合遺傳算法，優(yōu)化神經(jīng)網(wǎng)絡(luò)的初始權(quán)值。
  • Genetic algorithm is used to optimize the initial weight of back propagation network and the operation efficiency is enhanced
    用遺傳算法優(yōu)化bp網(wǎng)絡(luò)的初始權(quán)值,提高神經(jīng)網(wǎng)絡(luò)的運(yùn)算速度。
  • The initial weights of the neural network can be given according to the material meaning , which expedites the network convergence
    文中將神經(jīng)網(wǎng)絡(luò)與ip控制器結(jié)合，權(quán)的初始值可據(jù)其意義設(shè)定，大大加快了網(wǎng)絡(luò)的收斂速度。
  • In the control process uses two bp network . one is used as nni recognizing the model , another as neural network control device ( nnc ) . but first off - line recognizes controlled device , make sure nnc initial weights
    在控制的過程中,采用兩個(gè)bp網(wǎng)絡(luò),一個(gè)作為神經(jīng)網(wǎng)絡(luò)辨識(shí)器( nni )進(jìn)行辨識(shí)建模;另一個(gè)作為神經(jīng)網(wǎng)絡(luò)控制器( nnc ) 。
  • The algorithms for training weights update and constructing the target vectors are discussed . use the penalty term to improve the astringency of network . and study how choice the appropriate initial weights
    著重研究了根據(jù)輸入和輸出量合理選擇網(wǎng)絡(luò)結(jié)構(gòu),訓(xùn)練權(quán)值的更新算法,目標(biāo)向量的合理構(gòu)造,帶懲罰項(xiàng)的bp網(wǎng)絡(luò),改善了網(wǎng)絡(luò)的收斂性。
  • The dependences in multitemporal multispectral images by independent component analysis are reduced . in the algorithm , damped factor is imported to reduce the dependence on initial weights , thus the robust of the algorithm is improved
    在改進(jìn)的獨(dú)立成分學(xué)習(xí)算法中,通過在梯度下降方法中引入阻尼因子,降低了對(duì)初始值的依賴,提高了獨(dú)立成分求解的穩(wěn)健性。
  • During the course of develop fault diagnostic method , the influence to the training circle number with network structure 、 learning rate 、 initial weight value & door value etc are discussed . by comprehensive analyses and comparing , the comparatively rational value is adopted to be network ' s eigenvalue
    在制粉系統(tǒng)故障診斷樣本訓(xùn)練過程中，本文作者探討了網(wǎng)絡(luò)結(jié)構(gòu)、學(xué)習(xí)率、初始權(quán)值閾值等因素對(duì)訓(xùn)練速度的影響，為選取合理的網(wǎng)絡(luò)參數(shù)提供了依據(jù)。
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