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首页> 外文期刊>International journal of applied evolutionary computation >ANN Modeling of Motional Resistance for Micro Disk Resonator
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ANN Modeling of Motional Resistance for Micro Disk Resonator

机译:微型磁盘谐振器运动阻力的ANN建模

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This article describes how modeling is an integral part of design and development of any system that provides the theoretical characterization of the system and helps in understanding the relations between various parameters of the system, before the system is developed. The capability of an Artificial Neural Network (ANN) to model the complex relations between a set of inputs and outputs is exploited to model the motional resistance and resonance frequency for a contour mode disk resonator. The solution was to develop a multilayer feed forward neural network. The data set required to train the ANN is obtained by developing an electrical equivalent model and through the MEMS simulation software Coventorware. The network is trained using a Levenberg Marquardt algorithm. The number of hidden layers and the number of neurons in each hidden layer is optimized using a genetic algorithm. The ANN model developed an efficient model of the motional resistance and resonance frequency of the disk resonator. The ANN output is compared with the output of an electrical equivalent model and a reported fabricated structure.
机译:本文介绍了建模是如何在任何系统的设计和开发中不可或缺的部分,这些部分提供了系统的理论特性,并有助于在开发系统之前理解系统各个参数之间的关系。利用人工神经网络(ANN)对一组输入和输出之间的复杂关系进行建模的能力,可以对轮廓模式圆盘谐振器的运动阻力和谐振频率进行建模。解决方案是开发多层前馈神经网络。通过开发电气等效模型并通过MEMS仿真软件Coventorware,可以获得训练ANN所需的数据集。该网络使用Levenberg Marquardt算法进行训练。使用遗传算法优化隐藏层的数量和每个隐藏层中神经元的数量。 ANN模型建立了一个有效的磁盘谐振器运动阻力和谐振频率模型。将ANN输出与电气等效模型和报告的装配结构的输出进行比较。

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