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蚁群算法在地表隐伏断裂识别中的应用的探讨——以九寨沟景区为例
引用本文:李蓝蓝,段冰.蚁群算法在地表隐伏断裂识别中的应用的探讨——以九寨沟景区为例[J].西北地震学报,2019,41(4):970-977.
作者姓名:李蓝蓝  段冰
作者单位:平顶山职业技术学院, 河南 平顶山 467000,河南大学, 河南 开封 450044
基金项目:国家自然科学基金(71503070)
摘    要:在发震地区,准确识别地表断裂带可为地质与地震灾害预测提供基础数据。由于断裂带一般在地表出露是不连续的,在此对基于蚁群算法的地表断裂隐伏段的识别研究进行了尝试,基于遥感图像及航测数据,获取地形、地貌要素以及可以参考的其他要素,使用改进最短对角线方法提取断层表面的图像要素特征作为识别母体,在算法上依次将断裂带三角面片全部配对连接成四面体,再采用蚁群算法进行地表隐伏断裂空间识别。在九寨沟景区中进行了实例探讨,对2017年九寨沟地震的断裂进行尝试性识别,认为该方法可用来初步作为辅助识别地表断裂时的一个参考,同时基于本文方法与其他两种识别方法进行了分析对比。

关 键 词:地震灾区  地下断裂带  蚁群算法  断裂带识别  四面体
收稿时间:2018/10/21 0:00:00

Application of the Ant Colony Algorithm on the Identification of Surface Buried Faults: A Case Study of Jiuzhaigou Scenic Spot
LI Lanlan and DUAN Bing.Application of the Ant Colony Algorithm on the Identification of Surface Buried Faults: A Case Study of Jiuzhaigou Scenic Spot[J].Northwestern Seismological Journal,2019,41(4):970-977.
Authors:LI Lanlan and DUAN Bing
Institution:Pingdingshan Vocational and Technical College, Pingdingshan 467000, Henan, China and Henan University, Kaifeng 450044, Henan, China
Abstract:In a seismic area, the accurate identification of the surface fault zone can provide basic data for geological and seismic disaster prediction. In this paper, the recognition of the buried section of a surface fault is studied using the ant colony algorithm. Based on remote sensing image and aerial survey data, the terrain, geomorphological elements, and other elements are obtained. The improved shortest diagonal method is used to extract the image feature of the fault surface. All the triangular patches of the fault zone are matched and connected into tetrahedral in turn; then, the ant colony algorithm is used to carry out the spatial identification of the surface buried fault. Taking the Jiuzhaigou scenic spot as a case study, we discuss the fault identification of Jiuzhaigou earthquake in 2017. It is considered that this method can be used as a reference for the auxiliary identification of surface faults. Meanwhile, the proposed method is analyzed and compared with the other two identification methods.
Keywords:earthquake disaster area  underground fault zone  ant colony algorithm  fracture zone identification  tetrahedron
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