基于AHP耦合Sigmoid函数的重载铁路黄土边坡风险分析OA北大核心

Based on the transportation characteristics of heavy-haul railways with large axle load,high traffic and large capacity,the loess slope roadbed section has always been a high-risk section,and the existing risk assessment methods cannot realize the quantitative analysis of risks.In this paper,the method of AHP coupled Sigmoid function is used to quantitatively evaluate the risk of heavy-haul railways loess slope from the aspects of accident probability and accident loss.Firstly,based on the investigation of slope landslide accident and the stability control theory,the influencing factors of loess slope instability are clarified,and the stability evaluation model and slope instability hazard evaluation model are established.The analytic hierarchy method is applied to establish the index weights of the loess slope stability evaluation model,and the index assignment methods of influencing factors at all levels are proposed.The Sigmoid function based on Naive Bayes theory is introduced to construct the stable service probability,risk judgment matrix and risk level determination method.Finally,taking a high-steep loess slope of the Shuozhou-Huanghuagang Railway as the engineering background,the obtained theoretical method is applied to quantitatively analyze the risk,and the probability of instability of the slope is calculated to be 0.64,resulting in an economic loss of about 86.11 million CNY and falling at high-risk level.Specific prevention and control measures are proposed for low-score indicators such as slope geometrical characteristics,permeability and bedrock characteristics.