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Predicting the Performance of High-Speed Railway Bridge Using Regression Neural Network Approach

机译:使用回归神经网络方法预测高速铁路桥的性能

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The performance prediction of High-speed railway bridges (HSRB) is vital to detect the behavior of bridges under different train's speeds. This study aims to design a prediction model using the artificial neural network (ANN) to assess the performance of Yonjung high-speed bridge. A short-term health monitoring system is used to collect the behavior of bridge with different high-speed train's speeds. The statistical analysis is utilized to evaluate the bridge under speeds 165 to 403 Km/h. The evaluation of bridge and prediction model showing that the bridge is safe, and the ANN is shown a good tool can be used to estimate a prediction model for the displacement of bridge girder.
机译:高速铁路桥梁(HSRB)的性能预测对于检测不同列车速度下的桥梁的行为至关重要。本研究旨在使用人工神经网络(ANN)来设计预测模型,以评估Yonjung高速桥的性能。短期健康监测系统用于收集桥梁的行为,具有不同的高速列车的速度。利用统计分析来评估速度165至403 km / h的桥梁。桥梁和预测模型的评估表明桥是安全的,并且所示的ANN被示出了良好的工具可用于估计桥梁位移的预测模型。

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