基于联系云和改进冲突证据融合算法的泥石流易发性评价
Susceptibility evaluation based on connection cloud model and improved conflict evidence fusion method for debris flow disaster
陈光耀 1李司豪 1梁阳泽 1夏震昭 2徐照1
作者信息
- 1. 东南大学 土木工程学院,江苏 南京 211189
- 2. 华中科技大学 土木与水利工程学院,湖北 武汉 430074
- 折叠
摘要
泥石流作为一种常见的地质灾害,其形成机制复杂,影响指标众多且呈现多重不确定性,为综合考虑多种影响因素协同作用,基于信息融合和不确定性分析理论,提出一种基于证据理论和云模型的泥石流易发评价方法.首先,应用联系云模型(CCM)计算泥石流易发性关键评价指标的基本概率分配函数(BPA);然后,引入兰氏距离和邓氏熵,分别修正指标BPA的可信度和不确定度,得到修正后的BPA;最后,基于D-S证据理论对修正BPA进行证据融合,实现泥石流易发性评价,并进行实例验证.结果表明:所采用的CCM能够克服正态云模型计算BPA时要求指标为正态分布的缺陷,并考虑的指标分布的随机性和不确定性;提出的方法与其他 4 种常用的证据融合方法评价结果基本吻合,用于泥石流易发性评价有效可行;基于兰氏距离和邓氏熵改进的冲突证据融合算法可提高证据融合的收敛速度和精度,并且结果更准确可靠.
Abstract
Debris flow,as a common geological disaster,has a complex formation mechanism with numerous influencing factors and multiple uncertainties.To comprehensively consider the synergistic effects of various influencing factors,based on information fusion and uncertainty analysis theory,this paper proposed a debris flow susceptibility evaluation method based on evidence theory and cloud model.Firstly,the BPA function of key evaluation indicators for debris flow susceptibility was calculated using a connection cloud model.Subsequently,the reliability and uncertainty of the indicators'BPA were modified using Lance distance and DENG entropy,respectively,resulting in a corrected BPA.Finally,evidence fusion was performed on the corrected BPA based on Dempster-Shafer(D-S)evidence theory to achieve debris flow susceptibility assessment,followed by a case validation.The results show that the connection cloud model used in this paper overcomes the limitation that the normal cloud model requires indicators to follow the normal distribution when calculating BPA,and it considers the randomness and uncertainty of indicator distribution.The proposed method's evaluation results are generally consistent with those of four other commonly used evidence fusion methods,proving it to be effective and feasible for debris flow susceptibility evaluation.The conflict evidence fusion method improved based on Lance distance and DENG entropy can enhance the convergence speed and precision of evidence fusion,making the results more accurate and reliable.
关键词
联系云模型(CCM)/泥石流/易发性评价/基本概率分配函数(BPA)/冲突证据融合/兰氏距离/邓氏熵/证据理论Key words
connection cloud model(CCM)/debris flow/susceptibility evaluation/basic probability assignment(BPA)/conflict evidence fusion/Lance distance/DENG entropy/evidence fusion引用本文复制引用
基金项目
国家自然科学基金资助(72071043)
教育部人文社科基金资助(20YJAZH114)
江苏省自然科学基金资助(BK20201280)
江苏省研究生科研创新计划项目(KYCX23_0286)
出版年
2024
NETL
NSTL
万方数据