北中国平原地震带的脱群特征及其对概率性地震危险分析的影响
Jinmeng Bi1,2, Cheng Song3, Fuyang Cao3
1Tianjin Earthquake Agency, Tianjin, 300201, China. jinmengbi@126.com.
Scientific reports
|September 27, 2024
概括
准确的地震分类是地震模型的关键. 四种方法有效地消除余震,有助于地震危险分析和风险评估.
科学领域:
- 地震地震学 地震学
- 地质物理学 地质物理学
- 分析地震危害的分析.
背景情况:
- 准确识别背景地震活动对于地震建模和概率性地震危险分析 (PSHA) 至关重要.
- 了解地震事件集群和分类对于可靠的危险评估至关重要.
研究的目的:
- 评估和比较北中国平原地震带的四种不同的分类算法 (加德纳和诺波夫,雷森伯格,近邻,随机).
- 分析这些分类方法对概率地震危险分析 (PSHA) 的影响.
主要方法:
- 将四种不同的分类算法应用于北中国平原的地震数据.
- 优化算法输入参数使用科尔莫戈罗夫-斯米尔诺夫波桑分布测试.
- 与现有的地震区域地图进行分类的地震率和参数 (背景率,古堡-里赫特b值) 的比较.
主要成果:
- 四个测试的算法都有效地分离了地震数据,消除了唐山地震等重大事件的影响.
- 观察到大地震对分类特征 (时间,空间,强度) 的显著影响.
- 在算法和中国第五代地震地面运动参数划分地图之间发现了PSHA结果的差异.
结论:
- 分类算法显著影响PSHA结果,主要是通过它们对背景速率和古登堡-理查特b值的影响.
- 选择分类方法为地震风险评估,工程设计和灾害研究提供了关键的参考.
- 建议对算法效应进行进一步分析,以完善地震危险评估.
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