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