岩爆分类的支持向量机方法

Classification of rockburst using support vector machine

针对岩爆分类问题,提出了基于支持向量机的分类方法。通过对影响岩爆因素的分析,运用支持向量机理论建立岩爆类别的支持向量机模型。结果表明,基于支持向量机的岩爆分类方法具有较高的准确率,该方法是科学可行的,具有广泛的应用前景。

Rockburst is a disaster occurred usually in deep mines. Because of poor understanding of the mechanism, it is very difficult to give accurate classification using deterministic mechanical methods. A new method, therefore, was proposed. It was to use support vector machine to represent nonlinear relationship between rockburst and its factors. This model was learned from case histories and then could be used fast classification of rockburst for similar conditions. The support vector machine models have been established. The models gave accurate classification for the novel conditions. The results show this method is scientific, reliable, and promising.