支持向量机在围岩稳定性分类中的应用

在分析不同围岩稳定性分类方法及支持向量机算法的基础上，提出基于支持向量机的围岩稳定性分类方法。随后采用Matlab语言编程，建立了相应的围岩稳定性分类模型。以某蓄能电站一期工程的实例数据为学习样本，进行学习测试，得到训练效果较佳的分类模型，并用此模型对其二期工程的围岩进行了分类。分析中同BP神经网络算法进行了对比，结果表明，用支持向量机方法来进行围岩稳定性分类是可行的，且具有一定的优越性。

Application of support vector machine in classification of surrounding rock stability

A new method utilizing support vector machine is proposed for classification of surround rock stability and the model of classification based on Matlab language is developed. The classification data obtained from a pump-storage power station are used as the learning samples to train the model and then the model is applied to predict the classification of another project. The comparison of the predicted classification with the result by using BP neural network method shows that the proposed method is feasible.