Stability Analysis of High-Steep Mining Slope based on Clustering and Unascertained Measuring Method

Abstract

Ranging from geological, hydrological to geographical conditions, the influencing factors of the stability of high-steep mining slope involve lots of unascertained information which is difficult to analyze and judge with simple methods. Based on engineering analogy, this paper analyzes the stability of high-steep mining slope by clustering and unascertained measuring method. The clustering center of the various influencing factors of the stability of high-steep mining slope was pinpointed through dynamic clustering, with a large number of historical data as training samples. After using the unascertained measure to evaluate the numerous unascertained information, the authors put forward a new method for stability analysis of high-steep slope mine. The results show that the proposed algorithm can predict the steady state of high-steep mining slope with a hit rate above 90%. All in all, this research sheds new light on rational and rapid analysis of high-steep slope stability.