Data from: Predicting the maximum earthquake magnitude from seismic data in Israel and its neighboring countries

This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006–2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year.

本研究探讨了多种数据挖掘与时间序列分析方法，旨在基于同一区域既往记录的地震事件，预测未来一年内最大地震事件的震级。相关方法在1983年1月1日至2010年12月31日期间以色列及其邻国区域内发生的9042次地震事件目录中完成了评估。该数据集来源于以色列地球物理研究所（Geophysical Institute of Israel）。目录中的每一条地震记录均对应33个地震区域之一。研究人员已对数据进行清洗，剔除了前震与余震。本研究聚焦于活跃度最高的10个地震区域，这些区域的地震总数占该研究区域总地震数的80%以上。本研究的预测目标为：判断同一区域未来一年内的最大地震震级是否会超过该区域历年年度最大震级的中位数。由于本次分析的地震目录仅包含28年的完整观测数据，因此我们将每个区域的最后5条年度记录（对应2006年至2010年）划分为测试集，使用此前的年度记录作为训练集。预测特征基于古登堡-里克特比率（Gutenberg-Richter Ratio），以及若干基于各区域地震数量移动平均的新型地震活动性指标。实验结果表明，新型预测特征的实用性能远高于地震预测领域传统采用的各类指标。多目标信息模糊网络（Multi-Objective Info-Fuzzy Network，M-IFN）算法取得了最优预测精度，其曲线下面积（Area Under the Curve, AUC）为0.698；该算法同时考量了两个目标变量间的关联：同一年内的地震总数与最大地震震级。