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PERFORMANCE-LEVEL SEISMIC MOTION HAZARD ANALYSIS METHOD BASED ON THREE-LAYER DATASET NEURAL NETWORK

机译:基于三层数据集神经网络的性能级地震运动危害分析方法

摘要

A performance-level seismic motion hazard analysis method includes: (1) extracting seismic motion data and denoising the data; (2) extracting feature parameters from the data, and carrying out initialization; (3) generating a training set, an interval set and a test set; (4) training a multi-layer neural network based on the training set; (5) training output values of the neural network based on the interval set, and calculating a mean and a standard deviation of relative errors of the output values; (6) training the neural network based on the test set to determine output values, and calculating a magnitude interval based on an interval confidence; (7) carrying out probabilistic seismic hazard analysis to determine an annual exceeding probability and a return period of a performance-level seismic motion; and (8) determining a magnitude and an epicentral distance that reach the performance-level seismic motion based on the performance-level seismic motion and consistent probability.
机译:性能级地震运动危险分析方法包括:(1)提取地震运动数据并去噪; (2)从数据中提取特征参数,并执行初始化; (3)生成训练集,间隔集和测试集; (4)基于培训集培训多层神经网络; (5)基于间隔集的神经网络训练输出值,并计算输出值相对误差的平均值和标准偏差; (6)基于测试集训练神经网络以确定输出值,并根据间隔置信来计算幅度间隔; (7)进行概率地震危害分析,以确定年度超出概率和性能级地震运动的返回期; (8)确定基于性能级地震运动和一致概率基于性能级地震运动的幅度和震中距离。

著录项

  • 公开/公告号US2021302603A1

    专利类型

  • 公开/公告日2021-09-30

    原文格式PDF

  • 申请/专利权人 QINGDAO UNIVERSITY OF TECHNOLOGY;

    申请/专利号US202117211891

  • 发明设计人 WENFENG LIU;ZHENG ZHOU;JIANFENG LI;

    申请日2021-03-25

  • 分类号G01V1;G06N3/04;G06N3/08;G06N7;G01V1/30;

  • 国家 US

  • 入库时间 2022-08-24 21:22:13

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