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Application of artificial neural network technique to the formulation design of dielectric ceramics

机译:人工神经网络技术在介电陶瓷配方设计中的应用

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Application of artificial neural network (ANN) technique to the formulation design of BaTiO3 based dielectrics was carried through. Based on the homogenous experimental design the experimental results of 21 samples were analyzed by a three-layer back propagation (BP) network modeling. The results were also expressed and analyzed by intuitive graphics. Influence Of Co2O3 and Li2CO3 on the dielectric constant-temperature characteristic of BaTiO3-Nb2O5-La2O3-SM2O3 system was investigated. Optimized formulations were calculated and the optimized output values were in accordance with experiment results. It follows that the three-layer back propagation network based modeling proved to be a very useful tool in dealing with problems with serious non-linearity encountered in the formulation design of dielectric ceramics. (C) 2002 Elsevier Science B.V. All rights reserved. [References: 11]
机译:进行了人工神经网络技术在BaTiO3基电介质配方设计中的应用。基于均匀的实验设计,通过三层反向传播(BP)网络建模分析了21个样品的实验结果。结果也通过直观的图形表示和分析。研究了Co2O3和Li2CO3对BaTiO3-Nb2O5-La2O3-SM2O3体系介电恒温特性的影响。计算出最佳配方,并且最佳输出值与实验结果一致。由此可见,基于三层反向传播网络的建模被证明是非常有用的工具,可以解决介电陶瓷配方设计中严重的非线性问题。 (C)2002 Elsevier Science B.V.保留所有权利。 [参考:11]

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