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| 基于主成分回归分析的瓦斯含量预测 | |
| 引用本文： | 杨拉蒂,毕建武,贾进章. 基于主成分回归分析的瓦斯含量预测[J]. 世界科技研究与发展, 2013, 0(6): 694-696,732 |
| 作者姓名： | 杨拉蒂 毕建武 贾进章 |
| 作者单位： | 辽宁工程技术大学安全科学与工程学院,阜新123000 |
| 基金项目： | 辽宁省高等学校优秀人才支持计划（IJQ2011028）资助 |
| 摘 要： | 为了增加多元回归模型预测的精度，将主成分分析与多元回归分析相结合提出了PCA—MRA模型，并将该模型用于实际瓦斯含量预测。结果表明，PCA—MRA模型消除了输入变量之间的相关性，减少了输入变量值个数，提高了预测精度，便于实际推广和应用，为瓦斯含量预测提供一种新的途径。 |
| 关 键 词： | 安全工程 主成分分析 多元回归分析 煤层瓦斯含量 |
Prediction of Coal Seam Gas Content Based on Principal Component Regression |
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| YANG Ladi,BI Jianwu,JIA Jinzhang. Prediction of Coal Seam Gas Content Based on Principal Component Regression[J]. World Sci-tech R & D, 2013, 0(6): 694-696,732 | |
| Authors: | YANG Ladi BI Jianwu JIA Jinzhang |
| Affiliation: | ( College of Safety Science and Engineering, Liaoning Technical University, Fuxin 123000 ) |
| Abstract: | In order to predict coal seam gas content, a principal component analysis-multivariate regression analysis（PCA-MRA） mode is es- tablished, combined with the measured data. The results show that, coal seam gas content can be predicted effectively, avoiding complicating derivation and ealeulation. Compared with existing prediction methods, an intuitive and precise result is gotten,with computation time reduced significantly, exceedingly convenient for popularization and application. A novel approach for prediction of eal seam gas is provided. |
| Keywords: | safety engineering principal component analysis multiple regression analysis coal seam gas content |
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