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首页> 外文期刊>Journal of Earthquake Engineering >Generation of Multiple Earthquake Accelerograms Compatible with Spectrum Via the Wavelet Packet Transform and Stochastic Neural Networks
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Generation of Multiple Earthquake Accelerograms Compatible with Spectrum Via the Wavelet Packet Transform and Stochastic Neural Networks

机译：通过小波包变换和随机神经网络生成与频谱兼容的多个地震加速度图

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摘要

The principal purpose of this article is to present a novel methodology based on wavelet packet transform techniques and stochastic neural networks to generate more artificial earthquake accelerograms from available data, which are compatible with specified response spectra or the design spectra. The proposed method uses the decomposing capabilities of wavelet packet transform on earthquake accelerograms, and the learning abilities of stochastic neural network to expand the knowledge of the inverse mapping from response spectrum to coefficients of wavelet packet transform of earthquake accelerogram. This methodology results in a stochastic ensemble of wavelet packet transform coefficients of earthquake accelerograms and, they are used to the generate accelerograms applying the inverse wavelet packet transform. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to train and test the neural network, aiming at the demonstration of the method effectiveness.
机译：本文的主要目的是提出一种基于小波包变换技术和随机神经网络的新颖方法，以根据可用数据生成更多的人工地震加速度图，这些加速度图与指定的响应谱或设计谱兼容。该方法利用小波包变换对地震加速度图的分解能力和随机神经网络的学习能力，扩展了从响应谱到小波包变换对地震加速度图系数的逆映射知识。这种方法产生了地震加速度图的小波包变换系数的随机集合，并且它们被用于通过逆小波包变换来生成加速度图。最后，给出了一个解释性示例，该示例使用一组记录的加速度图来训练和测试神经网络，旨在证明该方法的有效性。

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