基于贝叶斯-粒子群算法的溜砂坡稳定性评价

P642.22; 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....

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Published in中国地质灾害与防治学报 Vol. 32; no. 2; pp. 53 - 59
Main Authors 娄超华, 田荣燕, 旺久, 孙威宇, 罗进
Format Journal Article
LanguageChinese
Published 西藏大学工学院,西藏拉萨 850000 01.04.2021
Subjects
拉萨市
粒子群算法
贝叶斯网络
稳定性评价
溜砂坡
Online AccessGet full text
ISSN1003-8035
DOI10.16031/j.cnki.issn.1003-8035.2021.02.07

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Abstract P642.22; 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.
AbstractList P642.22; 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.
Author 田荣燕
罗进
孙威宇
娄超华
旺久
AuthorAffiliation 西藏大学工学院,西藏拉萨 850000
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LUO Jin
WANG Jiu
TIAN Rongyan
SUN Weiyu
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Keywords 拉萨市
粒子群算法
贝叶斯网络
稳定性评价
溜砂坡
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Snippet P642.22; 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...
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Title 基于贝叶斯-粒子群算法的溜砂坡稳定性评价
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