At present, the weights of most evaluation indexes in fuzzy analysis methods of rock slope are a fixed value. However, the influence of the evaluation indexes on slope stability actually remains uncertain and fuzzy. As a result, if only the fixed weights are employed, it will disagree with the reality. To overcome the current problem, the cloud model method was introduced in the paper. In addition, the analytic hierarchy process (AHP) method for group decision based on confidence indexes was proposed to construct the cloud model of weight. In the meanwhile, the evaluation indexes, grading standards, grading intervals and cloud model characteristic parameters were determined by referring to the recommended China's industry standards and the experiences of previous researchers. On this basis, an application program was developed using Python language. The application was applied in the stability evaluation of a rock slope in Donghu Town, Lianjiang County, Fujian Province, China. According to the results, the slope was generally stable, but very unstable in some local areas. The result was highly or basically consistent with the result of CSMR, FLAC, AHP-TOPSIS, FSMR, or Fuzzy-AHP method as well as the actual situation on site, confirming the effectiveness of this evaluation method.

目前，岩质边坡模糊分析方法中大多数评价指标的权重都是固定值。然而，评价指标对边坡稳定性的影响实际上仍然是不确定和模糊的。因此，如果只采用固定的权重，则与实际情况不符。为了克服当前的问题，论文中引入了云模型方法。此外，提出了基于置信度指标的群决策层次分析法(AHP)构建权重云模型。同时，参考我国推荐的行业标准和前人的经验，确定了评价指标、分级标准、分级区间和云模型特征参数。以这个为基础，使用Python语言开发了一个应用程序。应用在福建省连江县东湖镇某岩质边坡稳定性评价中。结果表明，边坡总体上是稳定的，但在一些局部地区非常不稳定。结果与CSMR、FLAC、AHP-TOPSIS、FSMR或Fuzzy-AHP方法的结果以及现场实际情况高度或基本一致，证实了该评价方法的有效性。