针对模糊数学评价边坡稳定性中模糊隶属度和权重难以确定的问题，提出了对粗糙集理论中的属性商集作模糊统计求隶属度的集值统计方法。以神经网络正交试验得到的各因素对边坡稳定性影响级差之差为依据，构建AHP判断矩阵求权重，并引入了更适合于度量和决策的模糊积分理论。通过评价边坡样本与实例可知：模糊积分评价结果正确率与因素多少成正向关系，与其它理论方法结果和工程实际相一致。评价结果表明，该方法可行、结果可靠，而且计算过程更方便快捷。

To help determine the fuzzy membership degree and weight of fuzzy mathematics in  slope stability evaluation, we propose set-valued statistics for the degree of membership through fuzzy statistics of rough quotient set. Based on the range difference of factors affecting side slope stability obtained by neural network orthogonal analysis, we construct the judgment matrix through AHP (Analytic Hierarchy Process) to compute the weight, and introduce the fuzzy integral  theory which is more suitable for measurement and decision. Through the evaluation of slope samples and examples, we conclude that the accuracy of fuzzy integral evaluation results is in a positive correlation with the number of factors, and the results are consistent with those of other theoretical methods and engineering practices. This method is feasible, reliable, and the calculation process is more convenient.