# Risk Analysis of Service Slope Hazards for Highways in the Mountains Based on ISM-BN
## 6 Conclusions  
Highway slopes are inevitably subject to varying degrees of disaster risk while exerting great engineering benefits during the long-term operation. These risks may pose a serious threat to traffic safety and infrastructure stability. To effectively mitigate the occurrence of slope disaster accidents on operational expressways in mountains, the paper proposes a quantitative analysis method based on ISM and BN. The proposed method systematically analyzes the disaster risk of soil excavated slopes, identifying critical influencing factors and their correlations. This methodology provides actionable insights for risk control and disaster prevention. Based on the historical disaster information of service slopes and the relevant research literature, a total of 25 factors affecting the disaster risk were identified from four aspects, namely, environmental factors, slope technical conditions, disaster-bearing sets, and management factors by means of fishbone analysis. A risk impact factors list was established, thereby enriching the methodological framework for risk factor identification for slope disasters in mountainous operational highways. This advancement fills critical gaps in current research regarding comprehensive risk factor identification, establishing a substantial theoretical and practical basis for future studies on slope disaster risk assessment and mitigation strategies in mountainous highway environments. Apply the ISM-BN method to construct a slope disaster risk assessment model for mountainous highways. Through the multi-level directed interpretation structural model of ISM, the hierarchical relationships and interaction pathways among influencing factors are revealed. Leveraging BN's probabilistic reasoning capabilities, it quantitatively assesses node state probabilities, importance measures, sensitivity indices, and risk transmission pathways strength, enabling dynamic analysis and quantitative evaluation of risk evolution processes. Furthermore, the research introduces a novel fuzzy number-based method for calculating root node prior probabilities and incorporates the Leaky Noisy-Max model for conditional probability table determination, significantly enhancing model applicability and accuracy. Compared with conventional analytical approaches, the integrated ISM-BN methodology provides a more comprehensive framework for characterizing multi-factor interactions and their impacts on risk evolution within complex systems, establishing a new paradigm for slope disaster risk assessment. Taking the soil-cutting slopes of operational highways in mountainous areas of Anhui Province as an example, the simulation analysis and empirical validation of the constructed risk assessment model were conducted. It was found that engineering geological conditions \(X_{1}\), micro-topography and landform \(X_{3}\), and minimum monthly average temperature \(X_{6}\) were the key risk factors affecting in-service earth excavation slope hazards, and annual precipitation \(X_{4}\), daily maximum rainfall \(X_{5}\), and possible damage to in-road facilities \(X_{21}\) had a greater potential impact on it, which can be targeted for prevention and control in daily maintenance. These findings provide targeted guidance for routine maintenance and risk management of expressway slopes in mountainous areas. Further analysis revealed a strong correlation between the model's outputs and field-based risk assessment results, confirming the model's applicability and reliability. This research not only deepens the understanding of slope disaster risk evolution mechanisms but also provides theoretical support and practical guidance for safety operations and disaster prevention in mountainous expressways. The integrated ISM-BN analytical method enables the effective identification of high-risk factors and optimization of risk management strategies, thereby reducing the probability of slope disasters andenhancing the operational safety of highway systems. Nevertheless, there are several limitations that warrant consideration.