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Modeling and optimization of ITO/A1/ITO multilayer films characteristics using neural network and genetic algorithm

机译:基于神经网络和遗传算法的ITO / A1 / ITO多层膜特性建模与优化

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摘要

In this paper, ITO/A1/ITO multilayer films are fabricated with the variations of Al film thickness ancK annealing temperature. The effects of Al film thickness and annealing temperature on sheet resistance, optical transmittance, and the figure of merit are analyzed in the aid of the artificial neural network (NNet) models. In order to verify the fitness of NNet model, the root mean square error (RMSE) of training and testing data are calculated. The NNet models well represent the measured sheet resistance, optical transmittance, and the figure of merit. After NNet model is established, genetic algorithm (GA) is used to find the optimum process condition for the IT0/A1/IT0 multilayer films to obtain maximum figure of merit in the design space.
机译:本文根据Al膜厚和退火温度的变化制备了ITO / A1 / ITO多层膜。借助人工神经网络(NNet)模型分析了Al膜厚度和退火温度对薄层电阻,光学透射率和品质因数的影响。为了验证NNet模型的适用性,计算了训练和测试数据的均方根误差(RMSE)。 NNet模型很好地表示了测得的薄层电阻,光学透射率和品质因数。在建立NNet模型后,使用遗传算法(GA)来找到IT0 / A1 / IT0多层膜的最佳工艺条件,以在设计空间中获得最大的品质因数。

著录项

  • 来源
    《Expert Systems with Application》 |2012年第10期|p.8885-8889|共5页
  • 作者单位

    Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea;

    Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea;

    Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea;

    Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    ITO/AI/ITO; multilayer films; figure of merit; neural network; genetic algorithm;

    机译:ITO / AI / ITO;多层膜;功绩神经网络;遗传算法;

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