震级加权四指标Blade算法及在地震带识别中的应用

Blade算法的产生是根据地震点的分布寻找地震断层，其优势在于能从较稀疏的点分布中找出线型条带模式，但不足的是完全不考虑地震的震级屑性。针对Blade算法的几个不足之处逐步改进，提出了震级加权四指标Blade算法。算法主要的改进体现在：①引入以震级为变量的权重函数，体现了高震级地震的控制作用，通过模拟与实例比较了三种权重函数的效果；②改进原方法中所挑出的Blade中心必须有地震点，引入四指标评价体系代替原方法的二指标评价体系，同时还根据指标值将挑选出的线型条带修正到更淮确的位置。将原算法与改进算法应用于华北地区4级以上的地震数据集以按寻地震带，结果表明，震级加权四指标Blade算法较Blade算法有显改进，取得了较好的应用效果。

The MS-weighted 4-index blade algorithm and its application for identifying the seismic belts in the Great North China

The aim of the Blade algorithm is to search the seismic fault based on the distribution of earthquakes. It can find stripe pattern from sparse epicenter distribution. But the complete ignorance of the most important attribute of earthquakes, and the seismic moment is its obvious shortcoming. This paper improves the Blade algorithm step by step and develops the Ms-weighted 4 index Blade algorithm. The main improvements of the Ms-weighted 4-index Blade algorithm include:(1) The Ms-weighted function is introduced for showing that stronger earthquakes have more effects on index. We compare the effects of three Ms-weighted functions through simulation and application. (2) The blades selected out by the Blade algorithm must have an earthquake as the center. This is disadvantage of accurate location of the blade results. The 4-index evaluation is instead of the 2-substituting index in the Blade algorithm so that the selected-out blades can be amended for more accurate position by the evaluation index and the evaluation is more efficient. The Blade algorithm and the improved algorithms are applied to find the seismic belts based on the earthquakes (Ms>4. 0) in the North China. The comparison of the results shows that the Ms-weighted 4-index Blade algorithm has more notable improvement than the Blade algorithm and obtains the satisfactory result.