[1]郭少文,雷奇果,周 坤.极震区烈度的ELM预测模型[J].华南地震,2022,(01):140-146.[doi:10.13512/j.hndz.2022.01.19]
 GUO Shaowen,LEI Qiguo,ZHOU Kun.Seismic Intensity Prediction Model in Meizoseismal Area Based on ELM[J].,2022,(01):140-146.[doi:10.13512/j.hndz.2022.01.19]
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极震区烈度的ELM预测模型()
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华南地震[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2022年01期
页码:
140-146
栏目:
土木工程防震减灾
出版日期:
2022-03-30

文章信息/Info

Title:
Seismic Intensity Prediction Model in Meizoseismal Area Based on ELM
文章编号:
1001-8662(2022)01-0140-07
作者:
郭少文雷奇果周 坤
中交第二公路勘察设计研究院有限公司,武汉 430052
Author(s):
GUO ShaowenLEI QiguoZHOU Kun
Second Highway Consultant Co.,Ltd.,China Communications Construction Company ,Wuhan 430052,China
关键词:
地震震级震源深度极震区烈度ELM信息熵权重。
Keywords:
Earthquake magnitude Focal depth Seismic intensity in meizoseismal area ELM Information entropyWeight
分类号:
P315.9
DOI:
10.13512/j.hndz.2022.01.19
文献标志码:
A
摘要:
为了建立地震后极震区烈度快速预测方法,收集了2013年以前多次5级以上地震案例,以震级、震源深度作为输入参数,以极震区烈度作为输出参数,建立了ELM预测模型并分析震级和震源深度的信息熵和权重,该模型与现有广义线型模型预测精度提高约20%,主要结论如下:震级和震源深度与极震区烈度分别呈正相关和负相关性关系;震级的信息熵比震源深度的更大,其变异程度更小,包含的信息量更少,对极震区烈度的影响程度比震源深度更小;针对局部地区的专门预测模型和基于多参数的更加精确预测模型尚需努力。
Abstract:
In order to establish a rapid prediction method for the intensity in the meizoseismal area after the earthquake,the paper collects many cases of earthquakes with M ith before 2013. Taking the magnitude and focal depth as input parameters, and the seismic intensity in meizoseismal area as the output parameters, the paper establishes an ELM prediction model and analyzes the information entropy and weights of the magnitude and focal depth. Compared with the traditional model,the prediction accuracy of this model is improved by about 20 %.The main conclusions are as follows:there is a positive correlation between magnitude and focal depth,and a negative correlation between magnitude and seismic intensity. The information entropy of magnitude is higher than that of focal depth, which suggests that its variation degree and information content are less, and influence on seismic intensity is smaller. The effort to be done is to seek prediction means which is suitable for local area and based on multiple parameters.

参考文献/References:

[1]聂高众,徐敬海.基于震源深度的极震区烈度的评估模型[J].地震地质,2018,40(3):612-621.
[2]聂高众,安基文,邓砚.地震应急灾情服务进展[J].地震地质,2012,34(4):782-791.
[3] Davison C. On scales of seismic intensity and on the construction and use of isoseismal line[J]. BSSA,1921,11 (2):95-129.
[4]谢毓寿.新的中国地震烈度表[J].地球物理学报,1957,6 (1):35-47.
[5]胡聿贤.地震工程学(第二版)[M].北京:地震出版社, 2006:44-47.
[6]王德才,倪四道,李俊.地震烈度快速评估研究现状与分析[J].地球物理学进展,2013,28(4):1772-1784.
[7] Gutenber B,Richter C F. Earthquake magnitude,intensity, energy, and acceleration[J]. Bulletin of the Seismological, Society of America,1942,32(3):163-191.
[8]傅承义,刘正荣.论确定震源深度的宏观方法[J].科学记录,1960,4(5):350-354.
[9]许卫晓.烈度分布快速评估方法研究[D].哈尔滨:中国地震局工程力学研究所,2011.
[10] LAN Y,SOH Y C,HUANG G B. Ensemble of onl-inesequential extreme learning machine[J]. Neurocom-putting,2009(72):3391-3395.
[11]辛元芳,姜媛媛.改进的瓦斯突出预测模型[J].煤炭技术,2014,33(10):11-13.
[12]姜媛媛,刘柱,罗慧,等.锂电池剩余寿命的ELM间接预测方法[J].电子测量与仪器学报,2016,30(2):179-185.
[13] Blake A.On the estimation of focal depth from macroseismic data[J]. Bulletin of the Seismolgical Society of American, 1941,31(3):225-231.

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备注/Memo

备注/Memo:
收稿日期:2020-10-08
作者简介:郭少文(1986-),男,高级工程师,硕士,注册一级建造师(市政公用工程)、注册土木工程师(岩土),主要从事工程地质、水文地质方面研究。E-mail:394082124@qq.com
通信作者:雷奇果(1989-),男,工程师,工学学士,主要从事工程地质、水文地质方面研究。E-mail:419953628@qq.com
更新日期/Last Update: 2022-03-30