ABSTRACT
Slope instability warning is a complicated and comprehensive work. Slope stability is influenced by geological factors and engineering factors. The main methods to analyze slope stability are numerical analysis, physical simulation and intelligent analysis forecasting design. Compared with the former two, intelligent analysis can study multiple factors. The slope is used as the uncertainty and unbalanced complex system to consider, analyzing slope stability from several aspects. At present, fuzzy analysis (Wang,Y.M. 2011), grey theory (Zhou, N. et al. 2006), and extension theory (He, Z.M. et al. 2011) are widely used in intelligent analysis count model. There are many factors influencing the stability of open-pit mine slope. Most of the factors are fuzzy and random, and influence each other, which makes the relationship between variables very complex. It is difficult to use a mathematical equation to describe the relationship accurately (Qi, Z.F. et al. 2012). Therefore, it requires a process of slope instability warning that is dynamic and nonlinear and can handle both certain and uncertain information. Also, the process should objectively identify the stability state of the slope based on a number of existing engineering examples.
