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Seismic damage prediction of multistory building using GIS and Artificial neural network

机译:基于GIS和人工神经网络的多层建筑震害预测。

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An integrated GIS and Artificial neural network analysis model for earthquake-damaged, which couples geographic information systems(GIS) with artificial neural networks (ANN) to predict the seismic damage to multistory buildings based on earthquake intensity and adopt the peak acceleration value, is presented here. ANN is used to learn the patterns of development in the region and test the predictive capacity of the model, while GIS is used to develop the spatial, and perform spatial analysis on the results. The ANN combined with GIS was found to have a great potential to predict seismic damage.
机译:提出了一个集成的GIS和人工神经网络地震破坏分析模型,该模型将地理信息系统(GIS)与人工神经网络(ANN)结合起来,根据地震强度并采用峰值加速度值来预测多层建筑物的地震破坏。这里。人工神经网络用于学习该地区的发展模式并测试该模型的预测能力,而地理信息系统则用于开发空间,并对结果进行空间分析。结合GIS的ANN被发现具有预测地震破坏的巨大潜力。

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