|本期目录/Table of Contents|

[1]杨黎薇,林国良,邱志刚,等.基于人工神经元网络和多特征参数的预警震级估算*[J].地震研究,2018,41(02):302-310.
 YANG Liwei,LIN Guoliang,QIU Zhigang,et al.Study on Magnitude Estimation of Earthquake Early Warning Based on Various Characteristic Parameters and Artificial Neural Networks[J].Journal of Seismological Research,2018,41(02):302-310.
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基于人工神经元网络和多特征参数的预警震级估算*(PDF/HTML)

《地震研究》[ISSN:1000-0666/CN:53-1062/P]

卷:
41
期数:
2018年02期
页码:
302-310
栏目:
出版日期:
2018-04-20

文章信息/Info

Title:
Study on Magnitude Estimation of Earthquake Early Warning Based on Various Characteristic Parameters and Artificial Neural Networks
作者:
杨黎薇1林国良1邱志刚2江汶乡3王玉石4
(1.云南省地震局,云南 昆明 650224; 2.昆明学院,云南 昆明 650214; 3.中国铁道科学研究院铁道科学技术研究发展中心,北京 100081; 4.中国地震局地球物理研究所,北京 100081)
Author(s):
YANG Liwei1LIN Guoliang1QIU Zhigang2JIANG Wenxiang3WANG Yushi4
(1.Yunnan Earthquake Agency,Kunming 650224,Yunnan,China )(2. Kunming Vniversity,Kunming 650214,Yunnan,China)(3. Railway Science and Technology Research and Development Centre,China Academy of Railway Sciences,Beijing 10081,China)(4. Insititute of Geophysics,China Earthquake Administration,Beijing 10081,China)
关键词:
地震预警 震级估算 人工神经元网络 特征参数 线性拟合
Keywords:
earthquake early warning magnitude estimation artificial neural networks characteristic parameters linear fitting
分类号:
P315.9
DOI:
-
摘要:
预警震级测定是地震预警的关键技术环节之一。在满足地震预警系统时效要求的前提下,以国内现有的人工神经元网络构架为基础,考虑采用更多的特征参数,对实时持续计算确定预警地震震级的方法进行研究。通过对日本部分实际强震数据进行持续估算预警震级与实际震级间的偏差情况,对预警震级和实际震级进行线性拟合,提出对预警震级结果的修正公式,进一步完善本方法快速估算预警震级的准确程度。
Abstract:
The magnitude determination is the critical technology of earthquake early warning(EEW). With satisfying the timeliness requirements of the EEW system,this paper focuses on the research of magnitude real-time continuous determination considering adopting more characteristic parameters based on the current Artificial Neural Networks(ANN). We continuously calculate the deviation between estimation magnitude and the real magnitude by using partial strong motion records from Japan,and then suggest the revised model for estimation magnitude of EEW after linear fitting of those two magnitudes to further improve the accuracy of this fast magnitude estimation method.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-01-25
基金项目:国家自然科学基金——基于竖向台阵记录数据的强震动作用下土非线性动力特征的实证研究(3092)、中国铁道科学研究院科研项目(2017YJ137)、云南省科技计划项目(2017 FD088)以及昆明学院校级科研项目(XJL15007)联合资助.

更新日期/Last Update: 2018-04-23