| 基于最小二乘支持向量机的煤层底板突水量预测 |
| |
| 引用本文： | 姜谙男,梁冰. 基于最小二乘支持向量机的煤层底板突水量预测[J]. 煤炭学报, 2005, 30(5): 613-617 |
| |
| 作者姓名： | 姜谙男 梁冰 |
| |
| 作者单位： | 辽宁工程技术大学,力学与工程科学系,辽宁,阜新,123000;大连海事大学,交通工程与物流学院,辽宁,大连,116026;辽宁工程技术大学,力学与工程科学系,辽宁,阜新,123000 |
| |
| 摘 要： | 针对底板突水受到多种复杂因素的影响和突水量预测可看成是非线性、高维数、有限样本的模式识别问题，提出煤层底板突水量预测的最小二乘支持向量机方法，给出预测步骤，建立了符合期望风险最小化原则的预测模型，表达了最大突水量等级与其影响因素之间的非线性关系.
|
| 关 键 词： | 煤层底板 最大突水量 最小二乘支持向量机 |
| 文章编号： | 0253-9993（2005）05-0613-05 |
| 收稿时间： | 2005-01-10 |
| 修稿时间： | 2005-01-10 |
Forecast of water inrush from coal floor based on least square support vector machine |
| |
| JIANG An-nan,LIANG Bing. Forecast of water inrush from coal floor based on least square support vector machine[J]. Journal of China Coal Society, 2005, 30(5): 613-617 |
| |
| Authors: | JIANG An-nan LIANG Bing |
| |
| Affiliation: | 1. Department of Mechanics and Engineering Sciences, Liaoning Technical University, Fuxin 123000, China ; 2. College of Traffic Engineering and Logistics, Dalian Maritime University, Dalian 116026, China |
| |
| Abstract: | The water inrush from coal floor is affected by many complex factors.Forecast the maximum water inrush value is a nonlinear,high dimensional pattern recognition problem with limited samples.Aimed at the characteristics of the problem,presented a new method based on least square support vector machine.The maximum water inrush value's influent factors were selected as water pressure,water bearing formation,the thickness of confining strata,floor depth destroyed by mining,fault displacement.According to the predicting steps presented by this paper,the prediction model with minimum of structure risk was constructed and the complicated nonlinear relationship between the maximum water inrush value and its affected actors was presented well. |
| |
| Keywords: | coal floor maximum water inrush value least square support vector machine |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《煤炭学报》浏览原始摘要信息 |
|
点击此处可从《煤炭学报》下载免费的PDF全文 |
|
