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NEURAL NETWORKS METHOD IN PRESSURE GAUGE MODELING

机译:压力表造型中的神经网络方法

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The mathematical model of an acoustic wave field in the measuring cavity of pressure calibrator is established. Two ways to the problem solution are posed. The system of two neural networks -RBF and perceptron - is applied to the working hole optimization and the wave field approximation. This new approach based on neural networks methodology seems to be adequate, effective and powerful: it is weakly sensitive to some entrance data perturbation, it gives trained neural networks for a set of problems solution, it is possible to use the same ideas in case of nonlinearity modeling.
机译:建立了压力校准器测量腔中声波场的数学模型。提出了解决问题解决方案的两种方法。两个神经网络-RBF和Perceptron的系统应用于工作孔优化和波场近似。这种基于神经网络方法的新方法似乎是足够的,有效和强大的:它对某些入口数据扰动是弱敏感的,它为一组问题提供了训练的神经网络,可以使用相同的想法非线性建模。

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