A Novel Comprehensive Quantitative Method for Various Geological Disaster Evaluations in Underground Engineering: Multidimensional Finite Interval Cloud Model (MFICM)

Abstract The risk prediction of geological disasters exhibits extreme uncertainty and complexity due to the random distribution of evaluation indexes within a finite interval. To improve the accuracy of disaster prediction results, a new evaluation method is in this study suggested to perform a risk evaluation of geological disasters based on multidimensional finite interval cloud model (MFICM) and combination weighting. The MFICM with a transformation between qualitative concept and quantitative data depicts uncertainties and actual distribution features of indexes in the finite interval. Analytic hierarchy process (AHP) and principal component analysis (PCA) are adopted to determine the subjective and objective weights of evaluation indexes, respectively, and the combination weight is calculated by a linear method to reduce the influence of subjective factors. The numerical characteristic parameters of each indexes belonging to various risk levels are first calculated based on established evaluation index system. Subsequently, a multi-dimensional finite interval cloud is generated from a forward cloud generator using MATLAB software. Finally, the comprehensive certainty degrees relative to different levels for each sample are determined combined with combination weight, which achieves a mapping of uncertainty between semantic variables and index values. The proposed method is applied to engineering cases regarding three geological disasters, i.e., water inrush, rock burst and collapse. The obtained results with accuracy and results comparison with reference methods show that the MFICM is verified to be practical and universal for the risk evaluation of geological disasters, which improves and enriches the theoretical framework of geotechnical engineering disaster risk evaluation.