一种强震概率预测方法

地震 ›› 2003, Vol. 23 ›› Issue (3): 19-26.

一种强震概率预测方法

陈时军¹, 马丽², David Harte³, 王丽凤²

1.山东省地震局, 山东济南 250014;
2.中国地震局分析预报中心, 北京 100036;
3.新西兰统计学联合会, 新西兰惠灵顿 PO Box 12-649

收稿日期:2002-05-07 修回日期:2003-02-26 出版日期:2003-07-31 发布日期:2021-12-21
作者简介:陈时军(1963-), 男, 河南虞城人, 副研究员, 2000 年在读博士生, 现主要从事地震危险性预测、统计地震学等研究。
基金资助:
国家自然科学基金项目(40074013); 山东省自然科学基金项目(Y95E0670); 新西兰Marsden 基金项目(00-SRA-002-MIS)

A probabilistic method for strong earthquake prediction

CHEN Shi-jun¹, MA Li², David Harte³, WANG Li-feng²

1. Seismologi cal Bureau of Shandong Province, Ji′nan 250014, China;
2. Center for Analysis and Prediction, CSB, Beijing 300036, China;
3. St atistics Research Associates Limited, Wellington PO Box 12-649, New Zealand

Received:2002-05-07 Revised:2003-02-26 Online:2003-07-31 Published:2021-12-21

摘要/Abstract

摘要： 介绍了利用Logistic 回归进行地震危险性概率预测方法, 对以新西兰地区相同时间段内地震活动性b 值和等地震个数所覆盖空间区域的半径r 为例, 讨论了地震活动性参数的变化和强震发生的概率关系。研究表明, 该地区强震发生的概率总体上与强震发生前一年半时间窗内的地震活动性资料计算的b 值呈正相关关系, 与r 值呈负相关关系。该方法可以推广应用于研究其他异常分布和强震的概率统计关系。

关键词: Logistic 回归, 时空扫描, 概率预测, 强震

Abstract: By using Logistic regression, a probabilistic method for strong earthquake prediction has been introduced in this paper.The relation between seismic parameters and the probability of strong earthquake occurrence has been discussed by taking b value and r, the range of a given number of events covered in a given length of time sections in New Zealand as an example.Results show that the probability of strong earthquake occurrence has generally positive and negative correlation respectively for b value and r, which was estimated by events occurred in a time window of 1.5 year before strong earthquake occurrence.This method can be broadly applied to other anomaly distribution and the probabilistic relation of strong earthquake occurrence.

Key words: Logistic regression, Temporal-spatial scanning, Probabilistic prediction, Strong earthquakes

中图分类号:

P315.75

陈时军, 马丽, David Harte, 王丽凤. 一种强震概率预测方法[J]. 地震, 2003, 23(3): 19-26.

CHEN Shi-jun, MA Li, David Harte, WANG Li-feng. A probabilistic method for strong earthquake prediction[J]. EARTHQUAKE, 2003, 23(3): 19-26.

参考文献

[1] 张国民.我国地震监测预报研究的主要科学进展[J].地震, 2002, 22(1):2-8.
[2] 魏光兴, 刁守中, 周翠英.郯庐带地震活动性研究[M].北京:地震出版社, 1993.180-193.
[3] 梅世蓉, 冯德益, 张国民, 等.中国地震预报概论[M].北京:地震出版社, 1993.498.
[4] 王晓青, 傅征祥, 张立人, 等.中长期时空增益综合预测模型及其初步应用[J].地震学报, 2000, 22(1):45-53.
[5] Utsu T.Probabilities in earthquake prediction[J].Zisin Ser, 1977, 30(2):179-185.
[6] Greene, William H.Econometric Analysis[M], 3rd Ed.New Jersey:Prentice Hall, 1997.432.
[7] Want M Q, Eddy J M, Eugene C F.Application of odds ratio and logistic models in epidemology and health research[J].Health Values, 1995, 19:59-62.
[8] Harte D, Dong F L, Vreede M, et al.Quantifying the M8 algorithm Ⅱ:model, forecast and evaluation[M]. Victoria University Research Report, 2002.1-23.
[9] Thomas P M.Algorithms for maximum-likelihood logistic regression[M].Carnegie Mellon University Statistics Tech.Report 758, 2001.1-15.
[10] Harte D.Document for the Statistical Seismology Library[M].Research Repor, School ofMathematics and Computing Sciences, Victoria University of Wellington, 2001.1-162.
[11] Wiemer S, Zún iga R F.ZMAP-a software package to analyze seismicity[J], EOS, Transactions, Fall Meeting, AGU, 1994, 75:456.
[12] 马鸿庆.华北地区几次大震前的b 值异常变化[J].地球物理学报, 1978, 21(3):33-46.
[13] Aki K.A probabilistic synthesis of precursory phenomena[A].In:Simpson D W, Richards P D.Earthquake Prediction-An international Review[C].Washington D C:AGU, 1981.569-578.
[14] Ustu T.Long-term and short term seismic risk prediction estimationfrom seismicity and precursors[A].In:The organizing committee of ISCESP ed.A Collection of papers of International Sysposium on Contenal Seismicity and Earthquake Prediction[C].Beijing:Seismological Press, 1984.818-827.
[15] Kenji M, Akio Y.A probabilistic estimation of earthquake occurrence on the basis of the appearance times of multiple precursory phenomena[J].J Phys Earth, 1990, 38:431-444
[16] 王晓青, 傅征祥, 张立人, 等.中长期时空增益综合预测模型及其初步应用[J].地震学报, 2002. 22(1):45-53.
[17] 刘杰, 庄建仓, Vere-Jones D, 等.地震统计模型的年概率增益评估[J].地震学报, 2000.22(1): 35-44.