ROUGH SET AND SUPPORT VECTOR MACHINE BASED METHOD FOR EVALUATION OF ROCK SLOPE STABILITY

This paper uses the attribute reduction algorithm of rough sets and the classify function of support vector machines to establish a model of rock slope stability evaluation. At first, the rough set theory is used to acquire the knowledge of classification, which includes decision table construction, attribute discretization, attribute importance ranking, attribution reduction and rule abstract. Then, the key components are extracted as the input of support vector machine. The method can reduce the dimensions of the data and the complexity, and raises the efficiency of training and the accuracy of prediction. The effect extent to the slope stability of these factors can be obtained. The analyzed results show that this method can predict stability and destroy style of slope. 