摘要
致灾因素可划分为孕灾环境因素及诱发因素,通过1︰2000比例尺对衢州市溪口镇进行野外调查,并对该镇的各项致灾因素进行分析。结合综合指数法和BP神经网络建立溪口镇致灾因素与地质灾害易发性之间的非线性映射关系,完成定性-定量分析,优化各致灾因素的权重等参数,构建溪口镇地质灾害易发性预测模型。结果表明:溪口镇地质灾害易发性模拟结果很好地实现了溪口镇地质灾害易发性的可视化空间预测,本文模型具有推广应用价值。
The disaster-causing factors could divide into environmental factors and triggering factors.A field survey of Xikou Town,Quzhou City was carried out at a high precision scale of 1︰2000,and each disaster-causing factor in the study area was analyzed.We established the nonlinear mapping relationship between disaster-causing factors and geological disaster susceptibility combined comprehensive index method with BP neural network for qualitative-quantitative analysis.Then we optimized the weight of each disaster-causing factors to build up a prediction model of geological disaster susceptibility in Xikou Town.The result shows that the simulation results are well realized a spatial visualization prediction of geological disasters susceptibility in Xikou Town.and the model in this paper is worthy of popularization and application.
作者
赵国梁
姜纪沂
李巨宝
苏占东
袁浩巍
杨毅梦
ZHAO Guoliang;JIANG Jiyi;LI Jubao;SU Zhandong;YUAN Haowei;YANG Yimeng(School of Ecological Environment,Institute of Disaster Prevention,Sanhe 065201,China;Zhejiang Geological Exploration Institute,General Administration of Metallurgical Geology of China,Quzhou 324000,China;School of Water Resources and Environment,Hebei Geological University,Shijiazhuang 050031,China)
出处
《防灾科技学院学报》
2022年第3期68-79,共12页
Journal of Institute of Disaster Prevention
基金
中央高校基本科研业务费研究生科技创新基金资助(ZY20220306)
地质调查计划项目(DD20190216)。
关键词
地质灾害
致灾因素
易发性
综合指数法
BP神经网络
geological disaster
disaster-causing factor
susceptibility
comprehensive index method
BP neural network
