Unsupervised Pattern Recognition for Geographical Clustering of Seismic Events Post MW 7.8 Ecuador Earthquake

J. Parraga-Alava, G. Garzón, Roberth Alcivar Cevallos, Mario Inostroza-Ponta
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引用次数: 2

Abstract

Ecuador is located at the collision point of Nazca and South America tectonic plates, an area with high seismic activity; hence it is common that a large number of seismic events occur annually. On April 16, 2016, a Mw 7.8 earthquake impacted coastal Ecuador, and plenty of aftershocks were located within the affected and surrounding areas. Determining similar seismic geographical zones of the such events has become a problem of great interest for post-earthquake mitigation actions. In this paper, we present an approach to cluster seismic events post Mw 7.8 Ecuador earthquake. We carried out unsupervised pattern recognition through a clustering algorithm called MST-kNN. Our approach identified five clusters with similar seismic geographical zones along coastal provinces and Pacific Ocean. The results can be used to plan post-earthquake mitigation strategies such as identifying safe roads for evacuation plans or adequate location of ad hoc health and supply centers.
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厄瓜多尔7.8级地震后地震事件地理聚类的无监督模式识别
厄瓜多尔位于纳斯卡和南美构造板块的碰撞点,是一个地震活动频繁的地区;因此,每年发生大量地震事件是很常见的。2016年4月16日,厄瓜多尔沿海地区发生里氏7.8级地震,受灾地区及周边地区多次发生余震。确定此类事件的相似地震地理带已成为震后减灾行动中一个非常感兴趣的问题。在本文中,我们提出了一种方法,以集群地震事件后厄瓜多尔Mw 7.8地震。我们通过一种称为MST-kNN的聚类算法进行无监督模式识别。我们的方法确定了沿海省份和太平洋沿岸具有相似地震地理带的五个集群。研究结果可用于规划震后减灾战略,如确定疏散计划的安全道路或临时卫生和供应中心的适当位置。
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