## 5 Discussions  
Generally, a greater weight value indicates that an attribute or a subattribute is more intimately correlated with the stability of a slope. The determined weight vector for the three attributes (0.6, 0.2, 0.2) shows that the rock mass characteristics play the most important role in the stability of slopes, which agrees with the common understanding that the physical, mechanical, and geological properties of rock masses govern the stability of rock slopes [4; 8; 14; 17; 25; 46; 47]. Meanwhile, among the three subattributes of the rock mass characteristics, rock structure has greater importance over other two indexes, which is in line with the actual situation that most studied instable slopes are formed by bedding structures with multiple joint sets [59]. Moreover, the plant cover is particularly important in the topographic features, which agrees with the fact that most failed slopes in the studied area are barely covered by plants mainly due to human activities such as quarrying, and road and house constructions as demonstrated by the Daoxu Town quarry slope. Although the precipitation and seismic intensity are almost identical for all the studied slopes given the limited area selected, the precipitation seems to have greater importance than the seismic intensity. In situ survey showed that the majority of failure incidents of studied slopes happened after heavy rainfalls, such as the Daoxu Town quarry slope, demonstrating the important role precipitation plays in the stability of slopes. The maximum daily precipitation may be a better parameter for characterizing the influence of rainfall as long as the data are available. It is noted that the seismic intensity in Zhejiang Province is remarkably low, and no strong earthquakes have been recorded in recent 50 years.  
These results show that the rock slopes formed by bedding structures of fractured rocks disturbed by human activities and undergone heavy rainfall are most unstable, which are in concert with our common knowledge on slope stability [60; 61; 62]. The developed method can help quantitatively reveal the relative importance of different influencing factors, and help pinpoint the key factors that trigger instability of slopes. This could contribute to the policy-making regarding maintenance works of slopes.  
The above results and analysis indicate that the developed method holds a straightforward computational manner. Compared with other probabilistic methods such as ANN that typically require a complex learning process for updating stability knowledge [63; 64], the present method only requires a simple trial-and-error approach to determine the weight vector. Meanwhile, ANN requires a large amount of data that possess the main characteristics of a problem for learning and training, which need to be repeated when new data are included in the assessment. In contrast, the requirement of data amount is significantly small by the present method, making it suitable for application to regional slope stability assessment with limited geological survey data. Once an effective weight vector is determined, the method can be applied to the slopes of a whole region possessing similar geological background. Given the simplicity in computation and low demand on input data, this method, supported by expert opinion, can serve as a fast and reliable tool for regional stability assessment of rock slopes.