| 基于支持向量机的岩爆模式识别及预测 |
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| 引用本文： | 李素蓉,唐礼忠,白冰.基于支持向量机的岩爆模式识别及预测[J].长沙交通学院学报,2010,26(3):46-51. |
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| 作者姓名： | 李素蓉 唐礼忠 白冰 |
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| 作者单位： | 中南大学,资源与安全工程学院,湖南,长沙,410083 |
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| 基金项目： | 国家重点基础研究发展计划(973)项目 |
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| 摘 要： | 采用支持向量机,运用分析国内、外工程岩爆数据,以岩石单轴抗压强度与单轴抗拉强度的比值、洞室围岩的最大切向应力与岩石单轴抗压强度比值及弹性能量指数作为评判指标,对典型岩爆进行模式识别即分类,并进行了预测.试验结果表明,该预测方法具有较高的准确率,较好地解决了小样本及非线性等实际问题.
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| 关 键 词： | 岩爆 支持向量机 模式识别 预测 |
Pattern recognition and prediction of rockburst based on support vector machine |
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| LI Su-rong,TANG Li-zhong,BAI Bing.Pattern recognition and prediction of rockburst based on support vector machine[J].Journal of Changsha Communications University,2010,26(3):46-51. |
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| Authors: | LI Su-rong TANG Li-zhong BAI Bing |
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| Institution: | LI Su-rong,TANG Li-zhong,BAI Bing(School of Resources , Safety Engineering,Central South University,Changsha 410083,China) |
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| Abstract: | Based on the analysis of domestic and international projects data,a typical rockburst was predicted with support vector machine.The ratio of uniaxial compressive strength to uniaxial tensile strength of rock,the ratio of maximum tangent stress of adjoining rock to uniaxial compressive strength of rock,elastic energy index of rock were selected as a judge of indicators.The results show that this method is reliable and promising,and the model is very useful to solve the problems such as small sample and nonli... |
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| Keywords: | rockburst support vector machine pattern recognition prediction |
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