A Hierarchical Modular Fuzzy Model for Instability Susceptibility Assessment and Stabilization Decision Support in Rock Slopes
Journal
Applied Sciences
Publisher
MDPI AG
Date Issued
2026-08-03
Author(s)
Rodríguez-Servín, Marsella Gissel
Arreygue-Rocha, José Eleazar
Lobato-Báez, Mariana
Díaz-Barriga, José Manuel
Morales-Rosales, Luis Alberto
Type
Article
Abstract
Traditional rock mass evaluation methods have three main limitations: (1) their application depends largely on specialist judgment; (2) their discrete classification approach, such as RMR (Rock Mass Rating) and SMR (Slope Mass Rating), leads to abrupt transitions between categories; and (3) the interaction among geomechancial parameters is limited; these aspects reduce their ability to represent slope behavior in a gradual manner. The main objective of this research was to develop a model capable of representing gradual transitions between geomechanical conditions and the interaction among parameters related to susceptibility to instability. The model uses a hierarchical modular framework based on the Mamdani fuzzy inference mechanism, allowing the incorporation of expert knowledge through linguistic rules. It is implemented in a graphical environment that allows users to directly use geomechanical parameters obtained through conventional characterization or from three-dimensional digital models derived from UAV (Unmanned Aerial Vehicle) photogrammetry. Model consistency was evaluated through a sensitivity analysis, which verified the model’s response coherence across variations in input parameters. The graphical evaluation tool was then applied to three real case studies with different geomechanical configurations, and the results were compared with those from traditional methods (RMR and SMR). The results showed differences between traditional and fuzzy approaches, as our proposal links recommendations to specific geomechanical conditions across different evaluation levels, identifying conditions for potential intervention measures. In addition, the model enables the zonification of instability susceptibility, facilitating its use in future risk analyses. Our model is intended for application under normal slope conditions, without accounting for extreme events or external dynamic loads, such as seismic activity, groundwater level variations, infiltration, or high-mountain conditions. © 2026 by the authors.