首页 | 本学科首页   官方微博 | 高级检索  
     

逐步回归法在渗流观测资料分析中的应用
引用本文:杨国辉,周志维,马秀峰,喻蔚然.逐步回归法在渗流观测资料分析中的应用[J].江西水利科技,2016(4):235-238.
作者姓名:杨国辉  周志维  马秀峰  喻蔚然
作者单位:1. 江西省大余县水库工程管理局,江西 大余,341500;2. 江西省水利科学研究院; 江西省水工安全工程技术研究中心,江西 南昌330029
摘    要:逐步回归法能较好处理初选因子之间多重共线性问题,有效解决随机变量之间相关关系,确定显著变量因子。本文基于逐步回归法,结合实测资料进行回归分析,分析结果表明:利用逐步回归方法建立的回归模型拟合效果较好,复相关系数高,能较好反映水库大坝不同部位渗流显著影响因子;回归模型可用于进行水位预测,为了解大坝渗流运行状态提供指导和帮助。

关 键 词:渗流  逐步回归法  复相关系数  显著性影响因子

Application of stepwise regression method in seepage analysis
YANG Guo Hui,ZHOU Zhiwei,Ma Xiufeng and YU Weiran.Application of stepwise regression method in seepage analysis[J].Jiangxi Hydraulic Science & Technology,2016(4):235-238.
Authors:YANG Guo Hui  ZHOU Zhiwei  Ma Xiufeng and YU Weiran
Affiliation:;Dayu Reservoir Engineering Management Bureau of Jiangxi Province;Jiangxi Provincial Institute of Water Sciences,Jiangxi Engineering Technology Research Center on Hydraulic Structures;
Abstract:The stepwise regression can apply to deal with the problem of multiple co-linearity between primary factors,and solxe the correlation between random xariables,and determining the significant xariables. Based on the stepwise regression and combined analyzing measured data regression,the results showed that the fitting effect stepwise regression model is well,multiple correlation coefficient is large,reflecting the different significant influence factor and dexelop trend,predicting the water lexel with the regression model can proxide guidance for the understanding of the status of the dam seepage.
Keywords:Seepage  Stepwise regression method  Complex correlation coefficient  Significant influence factor
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《江西水利科技》浏览原始摘要信息
点击此处可从《江西水利科技》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号