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Neural network-based simulation for response identification of two-storey shear building subject to earthquake motion

机译:基于神经网络的两层剪切结构地震反应识别的仿真

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This article uses powerful technique of artificial neural network (ANN) models to simulate and estimate structural response of two-storey shear building by training the model for a particular earthquake. The neural network is first trained for a real earthquake data and the numerically generated responses of different floors of two-storey buildings as the training patterns. Trained ANN architecture is then used to simulate and test the structural response of different floors for various intensity earthquake data and it is found that the predicted responses given by ANN model are good for practical purposes. It is worth mentioning that although the simulation is done with numerically generated response data for particular earthquake, the idea may also be used for actual experimental (response) data.
机译:本文使用强大的人工神经网络(ANN)模型技术,通过训练特定地震的模型来模拟和估计两层剪切建筑物的结构响应。首先对神经网络进行训练,以获取真实的地震数据,然后将两层建筑物不同楼层的数字生成的响应作为训练模式进行训练。然后将训练有素的人工神经网络架构用于模拟和测试各种强度地震数据对不同楼层的结构响应,发现人工神经网络模型给出的预测响应非常实用。值得一提的是,尽管模拟是通过数字生成的特定地震的响应数据完成的,但该思想也可以用于实际的实验(响应)数据。

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