基于蚁群聚类算法的岩石边坡稳定性分析

由于岩石边坡影响因素众多且关系复杂，不能用简单的方法进行分析和判断。在工程类比的基础上，一般采用聚类的方法。但由于边坡工程问题环境的复杂性，岩石边坡稳定分析的聚类问题是一个复杂的模糊、随机优化问题，采用传统方法难免带来很多局限性。为了更好地解决这类问题，首次把蚁群聚类算法这种新近提出的仿生聚类算法引入岩石边坡工程领域，以解决其稳定分析问题，提出一种分析岩石边坡稳定问题的新方法。该方法在分析岩石边坡工程实例资料的基础上，采用蚁群聚类算法，以工程类比的思想判断岩石边坡的稳定状态。工程应用证明，该算法可以自动把岩石边坡分成几种类似的状态，判断准确率较高、计算速度较快，是一种比较实用的岩石边坡稳定分析方法，值得在岩石边坡分析领域推广应用。

Analysis of stability of rock slope based on ant colony clustering algorithm

For the influential factors of rock slopes are numerous and their relationship is very complicated; it can not be solved by traditional methods; so generally based on engineering analogy, the clustering methods are used widely. For the complicated environment influence of rock slopes, this clustering problem is a complicated fuzzy and random optimization problem; and it can not be solved by traditional methods very well. So, here a new bionics clustering optimization method, ant colony clustering algorithm, which is proposed recently, has been introduced into rock slope engineering field for the first time. Based on this new bionics clustering method, a new method for study stability of rock slope is proposed. Based on analyzing the data of rock slope samples, from the engineering analogy thinking by ant colony clustering algorithm, the stability of rock slopes can be estimated. The engineering application can prove that: this new algorithm can automatically sort the rock slope samples; and the validity is very high; the computing velocity is very rapid; so it is a very practical method for rock slope stability analysis; and it should be popularized.