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| 粗集与支持向量机联合建模及在开采沉陷预计中的应用 | |
| 引用本文： | 张安兵,高井祥,刘新侠,李喜盼.粗集与支持向量机联合建模及在开采沉陷预计中的应用[J].西安科技大学学报,2008,28(4). |
| 作者姓名： | 张安兵 高井祥 刘新侠 李喜盼 |
| 作者单位： | 1. 中国矿业大学环境与测绘学院,江苏,徐州,220186;河北工程大学资源学院,河北,邯郸,056021 2. 中国矿业大学环境与测绘学院,江苏,徐州,220186 3. 河北工程大学资源学院,河北,邯郸,056021 |
| 基金项目： | 国家自然科基金项目 ， 地理空间信息工程国家测绘局重点实验室开放基金 |
| 摘 要： | 地表沉陷与地质采矿因素之间存在复杂的非线性关系,人们通常采用概率积分法、神经网络等研究沉陷的规律性,但预计效果往往不够理想。本文采用粗集及支持向量机技术对其进行研究,首先应用粗集理论进行了岩移影响因素分析,给出了各影响因素的支持度,然后运用支持向量机预测技术构建了支持向量机预测模型。最后用实例进行了预测分析并与传统方法进行了对比,结论表明,本文建立的模型具有网络运行稳定、精度更高的优点。 |
| 关 键 词： | 粗集 支持向量机 沉陷预计 |
Subsidence predication method based on rough-set theory and support vector regression |
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| ZHANG An-bing,GAO Jing-xiang,LIU Xin-xia,LI Xi-pan.Subsidence predication method based on rough-set theory and support vector regression[J].JOurnal of XI’an University of Science and Technology,2008,28(4). | |
| Authors: | ZHANG An-bing GAO Jing-xiang LIU Xin-xia LI Xi-pan |
| Institution: | ZHANG An-bing1,2,GAO Jing-xiang1,LIU Xin-xia2,LI Xi-pan2 |
| Abstract: | Surface deformation is a complicated four-dimension spatial question,and the relation between geological mining factor and surface subsidence is nonlinear.Probability integration and artificial neural network are often used to study the law of surface deformation,but the prediction precise is not very good.This paper is studying it by rough-set theory and SVM.Rough-set theory is applied in analyzing working faces' subsidence observation data and the dependence relation between geological mining factor and surface subsidence is obtained on the basis of these data.Subsidence prediction model combining rough-set and SVM is established.The test samples reveal that the method is correct. |
| Keywords: | Rough set support vector regression subsidence prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |