ABSTRACT Seismic response analysis of layered soils which is gained from earthquake motion must be considered in practical engineering simulations. In order to predict this nonlinear dynamic response, artificial neural network (ANN) models were used in this research. The white noise earthquake was used as an induced earthquake to train and test a neural network against a numerical model (also subjected to the white noise earthquake). The numerical model was previously calibrated against field data from a specific earthquake. In order to ensure the accuracy of training, the nonlinear dynamic response of the optimal ANN model was tested against the field observation data from the specific earthquake. To validate the method's ability, the optimal model was subjected to nonlinear dynamic analysis under numerous earthquakes with different ground motions. The proposed model has shown high predicting performance for estimating soil dynamic deformations using the data obtained from the numerical software under different earthquake excitations. Furthermore, the model has been calibrated by matching the results obtained from the nonlinear seismic response with the response recorded under the actual earthquakes. The results suggested that the proposed model can be used as a suitable method for predicting nonlinear dynamic response of layered soils.

中文翻译：

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使用人工神经网络预测地震运动引起的层状土壤非线性动力响应

摘要 在实际工程模拟中必须考虑从地震运动中获得的层状土壤的地震响应分析。为了预测这种非线性动态响应，本研究中使用了人工神经网络 (ANN) 模型。白噪声地震被用作诱发地震，以针对数值模型（也受到白噪声地震）训练和测试神经网络。该数值模型之前是根据特定地震的现场数据进行校准的。为了保证训练的准确性，针对特定地震的现场观测数据，对最优ANN模型的非线性动力响应进行了测试。为了验证方法的能力，在多次不同地震动的地震下，对最优模型进行非线性动力分析。所提出的模型在使用从不同地震激励下的数值软件获得的数据来估计土壤动态变形方面显示出很高的预测性能。此外，通过将非线性地震响应的结果与实际地震下记录的响应进行匹配，对模型进行了校准。结果表明，该模型可作为预测层状土非线性动力响应的合适方法。通过将非线性地震响应的结果与实际地震下记录的响应进行匹配，对模型进行了校准。结果表明，该模型可作为预测层状土非线性动力响应的合适方法。通过将非线性地震响应的结果与实际地震下记录的响应相匹配，对模型进行了校准。结果表明，该模型可作为预测层状土非线性动力响应的合适方法。