论文标题
改进基于地震中长期记忆的地震预测模型
Improved Earthquake Forecasting Model Based on Long-term Memory in Earthquake
论文作者
论文摘要
地震的一个突出特征是他们的经验定律，包括时间和空间中的记忆（聚集）。基于地震经验定律，开发了几种地震预测模型，例如表演次要型余震序列（ETA）模型。然而，最近的一项研究表明，ETA模型在重现实际地震目录中发现的重要长期记忆特征方面失败了。在这里，我们将ETAS模型修改并概括为包括短期和长期触发机制，以说明数据中最近发现的短期和长期内存（指数）。我们的广义ETA模型准确地重现了意大利和南加州地震目录中观察到的短期和长期/距离记忆。还发现修订的ETAS模型可显着改善地震预测。
A prominent feature of earthquakes is their empirical laws including memory (clustering) in time and space. Several earthquake forecasting models, like the EpidemicType Aftershock Sequence (ETAS) model, were developed based on earthquake empirical laws. Yet, a recent study showed that the ETAS model fails in reproducing significant long-term memory characteristics found in real earthquake catalogs. Here we modify and generalize the ETAS model to include short- and long-term triggering mechanisms, to account for the short- and long-time memory (exponents) recently discovered in the data. Our generalized ETAS model reproduces accurately the short- and long-term/distance memory observed in the Italian and South California earthquake catalogs. The revised ETAS model is also found to significantly improve earthquake forecasting.
