基于贝叶斯-粒子群算法的溜砂坡稳定性评价  

Stability evaluation of sand slopes based on the Bayesian-PSO algorithm

作　　者：娄超华 田荣燕[1] 旺久 孙威宇 罗进 LOU Chaohua;TIAN Rongyan;WANG Jiu;SUN Weiyu;LUO Jin(College of Engineering,Tibet University,Lhasa,Tibet 850000,China)

机构地区：[1]西藏大学工学院,西藏拉萨850000

出　　处：《中国地质灾害与防治学报》2021年第2期53-59,共7页The Chinese Journal of Geological Hazard and Control

基　　金：西藏自治区重点科技计划项目(XZ201901-GB-14);西藏大学大学生创新创业训练计划项目(2018QCX016)。

摘　　要：溜砂坡具有突发、不易预测,且产生危害大的特点。文章对拉萨市周边实地调研测量收集数据,采集了12组具有代表性的溜砂坡灾害点数据集合,运用贝叶斯网络与粒子群算法相结合,并利用算法更新公式弥补单一算法的不足,引入信息熵分析了降雨量、坡度、坡高和植被覆盖率在算法中的权重,以及各因素对溜砂坡稳定性的影响,并对溜砂坡的稳定性进行了等级划分,实验证明该方法有效,对溜砂坡稳定性评价具有一定参考价值。Sand slide slope are sudden,unpredictable and has great harm.Through field investigations around Lhasa,12 representative data sets of sand slide slope disaster points were collected.By combining Bayesian network and Particle Swarm Optimization algorithm,and using algorithm update formula to make up for the short comings of the single algorithm,information entropy was introduced to analyze the weight of rainfall,slope,slope height and vegetation coverage in the algorithm.Then,the influence of various factors on the stability of sand-pass slope is analyzed and the stability of sand-pass slope is graded.Experiments proved that the method is effective and has certain reference value for the stability evaluation of sand slide slope.

关 键 词：溜砂坡 贝叶斯网络 粒子群算法 稳定性评价 拉萨市 

分 类 号：P642.22[天文地球—工程地质学]