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网络结构参数
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  network structure parameter
     It is found that the strength of CaO - bearing vitrified bonds is relative to the network structure parameter Y of the bonds.
     研究结果表明,含CaO结合剂的强度与结合剂的网络结构参数Y有关。
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     Analyzed are the network structure,parameter setting,hardware configuration and software composition,which ensure proper data communication between the Siemens-supplied PLCs and converters.
     通过分析网络结构,参数设定,硬件配置,软件组态来实现西门子PLC和变频器之间的数据通讯。
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  “网络结构参数”译为未确定词的双语例句
     Structural Parameters for Hydrogen Bonding Networks Formed in Systems of _(a_1)_(d_1)-A_(a_2)D_(d_2) Type
     _(a_1)_(d_1)-A_(a_2)D_(d_2)型氢键体系的网络结构参数
短句来源
     Statistical Parameters of Hydrogen Bonding Networks Formed in Solution of _f-A_aD_d Type
     _f-A_aD_d型氢键体系的网络结构参数
短句来源
     Network structure parameters of A_f-B_g type nonlinear free radical alternating copolymerization
     非线性A_f-B_g型自由基交替共聚反应的凝胶网络结构参数
短句来源
     The new network system functions the optimization seeking for parameters of the genetic algorithm performance, network structure and network performance and revision of the network value with GA-BP algorithm.
     该网络系统具有遗传算法性能参数优选、网络结构参数优选、网络性能参数优选以及GA—BP算法联合进行网络权值修改几种功能。
短句来源
     If the constant k is pre-determined, the heteregeneity factor Z of the inhomogeneous real networks could be evaluated fromZ = k(Q -1)(Q0-1)/[(1-k)(Q-1)-(Q0 - 1)]The proposed method was sucessfully applied o the characterization of the inhomogeneous network of divinylbenzene-styrene random copo ymer initiated by free radicals.
     当k已知时,测定非均一网络在良、劣两种溶剂中溶胀比Q~*和Q_0~*,依 Z=k(Q~*-1)(Q_0~*-1)/[(1-k)(Q~*-1)-(Q_0~*-1)],可得非均一因子Z及其他网络结构参数.
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  相似匹配句对
     The Construction of Network Firewall
     网络防火墙结构
短句来源
     Statistical Parameters of the Hydrogen Bonded Network
     氢键凝胶网络结构参数研究
短句来源
     Through optimization the structure and parameters of Elman recurrent neural network were defined.
     通过最佳化确定了Elman回归网络结构参数
短句来源
     By optimization, the structure and parameters of Elman recurrent neural network were defined.
     通过最佳化确定了Elman回归网络结构参数
短句来源
     With the samples trained, the structure and learning parameters of networks were optimized.
     进行网络训练和网络结构及学习参数优化;
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A Markov model of Delta network multiprocessor systems is presented, whic can be used to optimize construction parameters and task granularity of the system . The effects of the processor number, network construction parameters and task granularity on the processing power of the system are analyzed and the comparison of the results from the model with those from simulation is made,

本文建立了多级网络(δ-网)多处理机系统的马尔柯夫模型,为系统结构参数和任务粒度的选择提供了依据。文中分析了处理机数目、网络结构参数和任务粒度对系统性能的影响,并对模型计算结果和仿真结果作了比较。

The quotient of swelling ratio of homogeneous network in good solvent Q to that in poor solvent Qv satisfy the relationship Q/Q0 = 1+k(Q-1) in which k is a constant depending on the structure of the solvent and the monomer units of the network. If the constant k is pre-determined, the heteregeneity factor Z of the inhomogeneous real networks could be evaluated fromZ = k(Q -1)(Q0-1)/[(1-k)(Q-1)-(Q0 - 1)]The proposed method was sucessfully applied o the characterization of the inhomogeneous network of divinylbenzene-styrene...

The quotient of swelling ratio of homogeneous network in good solvent Q to that in poor solvent Qv satisfy the relationship Q/Q0 = 1+k(Q-1) in which k is a constant depending on the structure of the solvent and the monomer units of the network. If the constant k is pre-determined, the heteregeneity factor Z of the inhomogeneous real networks could be evaluated fromZ = k(Q -1)(Q0-1)/[(1-k)(Q-1)-(Q0 - 1)]The proposed method was sucessfully applied o the characterization of the inhomogeneous network of divinylbenzene-styrene random copo ymer initiated by free radicals. The variation of the estimated structural parameters are in accord with the prediction made from the mechanism of random copolymerization and network formation.

均一交联高分子网络在良溶剂和劣溶剂中平衡溶胀比Q和Q_0的比值依从Q/Q_0=1+k(Q-1)的关系,k是一个与溶剂性质和网络种类有关的恒定常数.当k已知时,测定非均一网络在良、劣两种溶剂中溶胀比Q~*和Q_0~*,依 Z=k(Q~*-1)(Q_0~*-1)/[(1-k)(Q~*-1)-(Q_0~*-1)],可得非均一因子Z及其他网络结构参数.用此方法研究了自由基引发的苯乙烯-二乙烯基苯无规共聚网络,所得结果符合聚合和网络形成机理的预计.

This paper begins with an introduction on back propagation neural network models including the structures of neural cells and the back propagation neural network as well as its learning algorithms and execution ,then proceeds to study the application of the model to well logging data for lithologic identification including the selection of network structure paramaters and training samples as well as the learning and operation of networks. At last, two data processing examples are cited to show the satisfactory...

This paper begins with an introduction on back propagation neural network models including the structures of neural cells and the back propagation neural network as well as its learning algorithms and execution ,then proceeds to study the application of the model to well logging data for lithologic identification including the selection of network structure paramaters and training samples as well as the learning and operation of networks. At last, two data processing examples are cited to show the satisfactory results achieved by applying the method.

本文首先介绍反向传播(BP)神经网络模型,包括神经元的结构、反向传播神经网络的结构、反向传播神经网络的学习算法和运行。然后介绍根据测井资料,应用反向传播神经网络模型作岩性自动识别的方法,包括网络结构参数的选择、学习样本的选取、网络学习和运行。最后,我们对二个实例进行处理解释,取得了比较满意的解释结果。

 
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