【摘要】 结合粗糙集和支持向量机两种智能算法,建立了基于粗糙集与支持向量机的岩质边坡稳定性评价模型。首先根据有限的经验数据建立属性决策表,通过属性约算法找出影响边坡稳定性的关键因素;然后将所提取的关键信息训练支持向量机。本文以铁路沿线边坡为例,进行边坡稳定性验算,结果表明算法能有效降低边坡稳定性影响因素集数据维数及支持向量机的复杂程度,提高训练速度和泛化能力。更多还原

【Abstract】 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.更多还原