Accelerometer Records
收藏arXiv2025-09-30 收录
下载链接：
https://github.com/brsylmz23/CNNLSTM_DeepEQ
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资源简介：
该数据集包含11,840条由EQTransformer（EQT）方法注释的加速度计数据记录，旨在预测强震动记录站在P波到达时间附近的平均剪切波速度（V_s30）。这些记录通过卷积神经网络（CNN）和长短期记忆网络（LSTM）的结构进行处理，同时利用了包括P波和S波到达时间在内的辅助信息。数据规模为11,840条记录，任务是从加速度信号中预测平均剪切波速度（V_S30）。
This dataset contains 11,840 accelerometer data records annotated by the EQTransformer (EQT) method, which aims to predict the average shear wave velocity (V_s30) of strong-motion seismic stations near the P-wave arrival time. These records are processed using architectures of convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, while auxiliary information including the arrival times of both P-waves and S-waves is utilized. The dataset totals 11,840 records, and the core task is to predict the average shear wave velocity (V_s30) from acceleration signals.
