摘要
针对常规动态聚类方法对初始聚类中心的敏感性以及聚类结果与样本输入次序有关等问题,提出了基于遗传算法的边坡稳定性评价的动态聚类方法,此方法对三峡库岸36个边坡的研究结果表明,该方法是一个具有全局最优解的动态聚类方法,其结果明显好于常规动态聚类方法。
In light of the problems of sensitivity to the original cluster center and clustering results depending on the order of input samples in the ordinary dynamic clustering method,a new dynamic clustering method for evaluation of slope stability is presented based on genetic algorithms.The method is applied to analyzing stability of 36slopes at banks of the Three Gorges Reservoir.Analyzing results show that the method is a dynamic clustering algorithm with global optimization and superior to the ordinary dynamic clustering algorithm.
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2002年第2期170-172,178,共4页
Rock and Soil Mechanics
基金
国家教育部高等学校骨干教师计划资助项目
关键词
边坡
稳定性评价
遗传算法
动态聚类
全局优化
数学模型
evaluation of slope stability
genetic algorithms
dynamic clustering
global optimization
