FCM聚类分析在公路边坡稳定性评价中的应用

在公路工程边坡稳定性评价过程中需要考虑很多因素的影响，这些影响难以用精确的数字来描述，因此很多情况下不适宜用定量的评价方法。鉴于此，主要采用FCM聚类分析方法研究公路边坡的稳定性评价，引入模糊聚类和改进的遗传算法，克服了传统FCM算法在模糊聚类分析中对初始化敏感的缺点，对于存在多个不确定因素的评价问题有明显的优势。通过实例分析表明，用该方法对公路工程中边坡稳定性评价是可行的、有效的。

Application of FCM Clustering in Highway Slope Stability Evaluation

The slope stability evaluation process in highway engineering needs to consider a lot of factors that are difficult to describe in precise figures, so it is not appropriate to use a quantitative evaluation method in many cases. Given this, this paper mainly adopts FCM clustering analysis method to study the evaluation of highway slope stability. Through the introduction of fuzzy clustering and improved genetic algorithm, it overcomes the shortcomings of the sensitive of traditional fuzzy clustering algorithm FCM analysis on the initialization, it has obvious advantages for the evaluation of multiple uncertainty factors. The proposed method for slope stability evaluation of highway projects is feasible and effective through a case study.