Results 11 to 20 of about 28,233 (257)
Modeling peak ground acceleration for earthquake hazard safety evaluation [PDF]
This paper presents a ground motion prediction (GMP) model using an artificial neural network (ANN) for shallow earthquakes, aimed at improving earthquake hazard safety evaluation.
Fatima Khalid, Milad Razbin
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Italian seismic amplification factors for peak ground acceleration and peak ground velocity
Ground motion modification over large areas is generally evaluated by focusing on source effects disregarding local lithostratigraphic site conditions. Hence, amplification maps of peak ground acceleration and peak ground velocity are proposed to improve
Amerigo Mendicelli +8 more
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Explainable Machine-Learning Predictions for Peak Ground Acceleration
Peak ground acceleration (PGA) prediction is of great significance in the seismic design of engineering structures. Machine learning is a new method to predict PGA and does have some advantages.
Rui Sun +3 more
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Prediction Model for Peak Ground Acceleration Using Deep Learning [PDF]
Over the last decade, several studies have been proposed in the field of earthquake early warning (EEW) systems. Deep learning can be used to determine the magnitude of earthquakes and predict the PGA (peak ground acceleration).
Hatem Ahmed +3 more
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Predicting peak ground acceleration using the ConvMixer networkKey points
The level of ground shaking, as determined by the peak ground acceleration (PGA), can be used to analyze seismic hazard at a certain location and is crucial for constructing earthquake-resistant structures.
Mona Mohammed +3 more
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Application of metaheuristic algorithms in prediction of earthquake peak ground acceleration
The seismic resilience of a structure has been evaluated using peak ground acceleration (PGA). Ground motion parameters such as source characteristics, local site conditions are used to forecast the PGA of the ground motion. This paper aims to develop an
Surya Prakash Challagulla +3 more
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Peak ground acceleration prediction for on-site earthquake early warning with deep learning [PDF]
Qingxu Zhao
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本文随机选取了100条具有不同地震动峰值特征参数的地震动记录,通过基线校正、积分等方法获取每条地震动的峰值加速度(PGA)、峰值速度(PGV)和峰值位移(PGD)三个参数,进而基于有限元数值模拟,通过对比同一个观测点不同峰值特征参数的特性与不同观测点同一峰值特征参数的特性来研究土坡的地震响应规律,分析各地震动峰值特征参数与土坡地震响应的相关性。计算结果表明:PGA,PGV和PGD与土坡地震响应都具有良好的正相关性,其相关性系数平均值分别为0.868,0.981,0.926 ...
Lurong Du +3 more
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Strong ground motions caused by earthquakes with magnitudes ranging from 3.5 to 6.9 and hypocentral distances of up to 300 km were recorded by local broadband stations and three-component accelerograms within Georgia’s enhanced digital seismic network ...
Nato Jorjiashvili +4 more
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Note on scaling of peak ground acceleration and peak ground velocity with magnitude [PDF]
SUMMARY The theoretical scaling of near-field peak ground acceleration and peak ground velocity with moment magnitude, Mw, is found using an L model of rupture. This scaling matches well with the magnitude scaling of recent attenuation relations.
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