Open-Pit Mine Slope Stability Clustering Analysis and Assessment Models Based on an Inverse Hyperbolic Sine Similarity Measure of SVNSs

Abstract

Slope instability is a common and typical problem of geological hazards, often accompanied by significant losses. So, it is necessary to provide some simple and effective methods to avoid the potential geological hazards of slope instability. It is obvious that the clustering and assessment of slope stability are very crucial. However, the existing clustering and assessment methods in the scenario of single-valued neutrosophic sets (SVNSs) imply some difficulties in engineering applications, such as a lot of collective sampling work, the complex training process, and the selection issue of different types of membership functions. Regarding these problems, this paper proposes an inverse hyperbolic sine similarity measure (IHSSM) of SVNSs and its netting clustering and assessment models for slope stability clustering analysis and evaluation based on the fuzzification process of the true, false, and uncertain Gaussian membership functions for slope sample data. Finally, the proposed clustering and assessment models are applied to the clustering analysis and assessment of 20 slope samples as the case study, and then comparing the results of clustering analysis and stability evaluation of the proposed models with those of the existing relative methods by the 20 slope samples, we verify the validity, consistency, and rationality of the proposed netting clustering and evaluation models.

Keywords

• single-valued neutrosophic set
• netting clustering method
• gaussian membership function
• similarity measure
• slope stability clustering analysis
• slope stability evaluation