Abstract
Slope evaluation is a basic geotechnical engineering issue. The rationality of index weight greatly affects the accuracy of evaluation results in the evaluation system. Furthermore, in practical engineering, some indexes can be considered random variables obeying a certain distribution. Traditional evaluation methods of slope stability ignore the effect of this index uncertainty. Therefore, it is necessary to obtain the evaluation results of slope stability reasonably by modifying the previous weighting methods and considering the uncertainty values of the indexes. A new method has been introduced to solve the problem mentioned previously based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Monte Carlo simulation (MCS). TOPSIS is used as a basic model for evaluating slope stability. TOPSIS and MCS are coupled to establish multiobjective optimization simulation model, which can search the more optimal and reliable weight. The optimal weight is then substituted into the TOPSIS basic model to calculate the status of slope stability. In this calculation process, MCS is introduced into the TOPSIS basic model to consider the uncertainty value of index. The new method of evaluating slope stability was demonstrated by taking a practical project as an example. Compared with other weighting methods, the coupled TOPSIS and MCS model can obtain the most reliable weight, and the reliability is 48.7%. Then, the evaluation of slope stability was examined with the certainty and uncertainty cases, respectively. The results demonstrate that the proposed new evaluation method is more realistic than the traditional methods for evaluating the slope stability. The new method has high accuracy and is easy to use.
Highlights
A New Evaluation Method for Slope Stability Based on TOPSIS and Monte Carlo simulation (MCS)Received November 2019; Revised January 2020; Accepted 28 January 2020; Published 19 February 2020
Instabilities of natural and cut slopes cause enormous loss of life, injuries, and damage to the property in every year
Some observations can be made based on the results presented in Table 3. e reliability of W obtained is 48.7% higher than the results obtained by other methods. erefore, the coupled TOPSIS and Monte Carlo simulation (MCS) model for determining the weight of index is feasible in this paper
Summary
Received November 2019; Revised January 2020; Accepted 28 January 2020; Published 19 February 2020. Traditional evaluation methods of slope stability ignore the effect of this index uncertainty. Erefore, it is necessary to obtain the evaluation results of slope stability reasonably by modifying the previous weighting methods and considering the uncertainty values of the indexes. TOPSIS is used as a basic model for evaluating slope stability. E optimal weight is substituted into the TOPSIS basic model to calculate the status of slope stability. In this calculation process, MCS is introduced into the TOPSIS basic model to consider the uncertainty value of index. E new method of evaluating slope stability was demonstrated by taking a practical project as an example. Compared with other weighting methods, the coupled TOPSIS and MCS model can obtain the most reliable weight, and the reliability is 48.7%. en, the evaluation of slope stability was examined with the certainty and uncertainty cases, respectively. e results demonstrate that the proposed new evaluation method is more realistic than the traditional methods for evaluating the slope stability. e new method has high accuracy and is easy to use
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
