| 基于支持向量机的矿区开采沉降的预测 |
| |
| 引用本文： | 景海河,叶欣,高彦东.基于支持向量机的矿区开采沉降的预测[J].黑龙江科技学院学报,2008,18(4). |
| |
| 作者姓名： | 景海河 叶欣 高彦东 |
| |
| 作者单位： | 黑龙江科技学院,建筑工程学院,哈尔滨,150027 |
| |
| 摘 要： | 针对矿区开采沉降预测方法问题,在分析了矿区开采沉降因素的基础上,利用统计学习的新方法--支持向量机,结合最小二乘算法,提出了矿区沉降的预测模型,预测结果与神经元网络,多项式拟合结果进行比较,结果表明支持向量机在沉降预测方面准确性高,泛化能力强.
|
| 关 键 词： | 支持向量机 沉降 预测 |
Subsidence prediction of diggings based on support vector machine |
| |
| JING Haihe,YE Xin,GAO Yandong.Subsidence prediction of diggings based on support vector machine[J].Journal of Heilongjiang Institute of Science and Technology,2008,18(4). |
| |
| Authors: | JING Haihe YE Xin GAO Yandong |
| |
| Institution: | JING Haihe,YE Xin,GAO Y,ong(College of Architecture , Civil Engineering,Heilongjiang Institute of Science , Technology,Harbin 150027,China) |
| |
| Abstract: | Directed at the subsidence prediction of diggings,this paper,based on the analysis of the factors of subsidence,presents an attempt to develop the forecast model of the subsidence,depending on the new statisticssupport vector machine,combined with least square.The comparison of the prediction results obtained in this way with those done with the neural networks and polynomial fit shows that the support vector machine performs with higher veracity and better extensiveness in case of subsidence prediction. |
| |
| Keywords: | support vector machine subsidence prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
