| 基于支持向量机的砂土液化预测分析 |
| |
| 引用本文： | 师旭超,郭志涛,韩阳.基于支持向量机的砂土液化预测分析[J].西北地震学报,2009,31(4):363-366. |
| |
| 作者姓名： | 师旭超 郭志涛 韩阳 |
| |
| 作者单位： | 河南工业大学土木建筑学院,河南,郑州,450052 |
| |
| 基金项目： | 国家自然科学基金资助项目，河南省高校青年骨干教师资助项目 |
| |
| 摘 要： | 将支持向量机方法应用于砂土地震液化预测问题.考虑影响砂土液化的因素,选用震级、标贯击数、相对密实度、土层埋深、地震历时、地面运动峰值加速度和震中距7个影响因子作为液化判别指标,建立了砂土液化预测的支持向量机模型.以砂土液化实测数据作为学习样本进行训练,建立相应函数对待判样本进行分类.研究结果表明:支持向量机模型分类性能良好,是砂土地震液化预测的一种有效方法,可以在实际工程中进行推广.
|
| 关 键 词： | 砂土 地震液化 支持向量机 预测 |
Analysis on Sand Seismic Liquefaction Prediction Based on the Support Vector Machine |
| |
| SHI?Xu-chao,GUO?Zhi-tao and HAN?Yang.Analysis on Sand Seismic Liquefaction Prediction Based on the Support Vector Machine[J].Northwestern Seismological Journal,2009,31(4):363-366. |
| |
| Authors: | SHI?Xu-chao GUO?Zhi-tao and HAN?Yang |
| |
| Institution: | Department?of?Civil?Engineering,?Henan?University?of?Technology;Department?of?Civil?Engineering,?Henan?University?of?Technology;Department?of?Civil?Engineering,?Henan?University?of?Technology |
| |
| Abstract: | Considering the main factors with important influence on sand seismic liquefaction, the support vector machine (SVM) model is established, which includes seven indexes such as earth-quake magnitude, SPT counts,relative density, soil layer depth, time history of earthquake, peak ground acceleration and epicenter distance. Taking surving data as samples for training and learn-ing, some functions are obtained in identification of sand sample. It is shown that the identifica-tion model of SVM analysis is an effective method to predict sand liquefaction with high prediction accuracy and could be used in practice. |
| |
| Keywords: | Sand Seismic liquefaction Support vector machine Prediction |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《西北地震学报》浏览原始摘要信息 |
| 点击此处可从《西北地震学报》下载免费的PDF全文 |
|
