Magnitude and neural networks

机译：幅度和神经网络

获取原文

获取原文并翻译 | 示例

页面导航

摘要
著录项
相似文献
相关主题

摘要

The article describes briefly how to use spectral method to calculate moment magnitude of seismic events and how to use the neural networks for magnitude calculations. It is suggested that the multitaper method should be used instead of the single window method. In the case of a neural network, the article shows how to pre-process the velocity seismogram to calculate magnitude by using a very small neural network.

机译：本文简要介绍了如何使用频谱方法来计算地震事件的矩震级以及如何使用神经网络进行震级计算。建议使用多锥度法代替单窗法。在神经网络的情况下，本文介绍了如何使用非常小的神经网络对速度地震图进行预处理以计算震级。

著录项

来源
《Joint Japan-Poland Symposium on Mining and Experimental Seismology, Nov, 1999, Kyoto, Japan》|1999年|p.355-363|共9页
会议地点 Kyoto(JP)
作者
J. NIEWIADOMSKI;
展开▼
作者单位

Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland;

展开▼
会议组织
原文格式 PDF
正文语种 eng
中图分类地球物理学;
关键词
magnitude; multitaper; neural network;

机译：幅度;多锥度;神经网络;

相似文献

外文文献
中文文献
专利

1. Comparing Artificial Neural Networks with Traditional Ground-Motion Models for Small-Magnitude Earthquakes in Southern California [J] . Klimasewski Alexis, Sahakian Valerie, Thomas Amanda Bulletin of the Seismological Society of America . 2021,第3期

机译：将人工神经网络与传统地面运动模型进行比较南加州小幅地震
2. Earthquake Magnitude Prediction Using Recurrent Neural Networks [J] . Jesús González, Wen Yu, Luciano Telesca Proceedings . 2019,第1期

机译：使用经常性神经网络预测地震幅度预测
3. Fault Parameters-Based Earthquake Magnitude Estimation Using Artificial Neural Networks [J] . Asim Khawaja M., Javed Farhan, Hainzl Sebastian, Seismological research letters . 2019,第4期

机译：基于故障参数的地震幅度估计使用人工神经网络
4. Speeding-up pruning for Artificial Neural Networks: Introducing Accelerated Iterative Magnitude Pruning [C] . Marco Zullich, Eric Medvet, Felice Andrea Pellegrino, International Conference on Pattern Recognition . 2021

机译：用于人工神经网络的加速修剪：引入加速迭代幅度修剪
5. Earthquake Magnitude Prediction Using Support Vector Machine and Convolutional Neural Network [D] . Amfo, Esther Kesewa. 2019

机译：使用支持向量机和卷积神经网络预测地震幅度预测
6. Resting‐state magnetoencephalography source magnitude imaging with deep‐learning neural network for classification of symptomatic combat‐related mild traumatic brain injury [O] . Ming‐Xiong Huang, Charles W. Huang, Deborah L. Harrington, 2021

机译：休息状态磁脑源幅度成像与深学习神经网络用于分类症状与症状相关的轻度创伤性脑损伤
7. Comparing Artificial Neural Networks with Traditional Ground-Motion Models for Small-Magnitude Earthquakes in Southern California [O] . Alexis Klimasewski, Valerie Sahakian, Amanda Thomas 2021

机译：将人工神经网络与传统地面运动模型进行比较南加州小幅地震

Magnitude and neural networks

摘要

著录项

相似文献

相关主题

期刊订阅