Evaluation And Prediction Of Slope Stability Based On Indeterminacy Mathematic Method

Landslide frequently occurs in China that threatens the people's life and property and economic construction greatly. With the rapid development of our modern construction, more and more high-steep and deep slopes appear in many engineering fields such as hydroelectricity, mine, harbor, road, railway and energy, etc. Therefore, how to analyze and evaluate slope stability reliably and effectively is very significant to slope safety and landslide forecast in theory and practice. This paper reviews the development actuality of slope stability research, indicates the shortcomings and development trend of various analytical methods and brings forward the research object and content. The results are obtained as follows:(1) Slope blocks are complex geologic bodies. Its mechanical property parameters,engineering properties and the distribution laws of the structure planes are very uncertain. Therefore, the attribute mathematics theory created by Prof. Cheng Qiansheng is introduced to slope stability analysis, and its application in economy and manages is very famous.(2) The fuzzy evaluation of slope stability is a promising method. But many concerned literatures process concept and definition absolutely based on fuzzy set theory in slope stability analysis, it makes the determination of membership function so difficult and subjective that seriously barriers the application of this kind of methods in engineering. Therefore, the engineering fuzzy sets theory created by Prof. Chen Shouyu is introduced to slope stability analysis, and its application in slope stability evaluation is studied by this paper.(3) Many engineering cases with clustering characteristics provide abundant knowledge for slope stability analysis. The fuzzy clustering interactive computing model presented by Prof. Chen Shouyu is applied to the clustering analysis of many engineering cases, and its incomplete convergence is indicated. For solving the problem the fuzzy similar clustering model is put forward by this paper on basis of fuzzy optimal theory. The calculation results show that the fuzzy similar clustering model can class the clustering samples naturally and avoid above mentioned problem.(4) The attribute recognition criterion and rank feature value criterion sometimes are subjective and unreasonable. Therefore, the connection number is introduced to improve them. The evaluation results has shown that the method is feasible,reasonable and effective.Lastly, the whole paper is summarized, and some promising problems are discussed.