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主成分回归在径流预测中的应用
引用本文:张丽,王悦钰,白雪莲. 主成分回归在径流预测中的应用[J]. 人民黄河, 2012, 34(5): 20-21,24
作者姓名:张丽  王悦钰  白雪莲
作者单位:华北水利水电学院,河南郑州,450011
摘    要:采取主成分回归方法对具有多重共线性的湘江流域43 a径流资料进行了分析,以实测径流量、降水量和蒸发量等7个指标进行了样本预测。结果表明:主成分回归比多元线性回归的误差小,预测值更接近于实测值。

关 键 词:多重共线性  主成分回归  多元线性回归  径流预测

Application of Principal Component Regression in Runoff Forecasting
ZHANG Li , WANG Yue-yu , BAI Xue-lian. Application of Principal Component Regression in Runoff Forecasting[J]. Yellow River, 2012, 34(5): 20-21,24
Authors:ZHANG Li    WANG Yue-yu    BAI Xue-lian
Affiliation:(North China University of Water Resources and Electric Power,Zhengzhou 450011,China)
Abstract:Based on the multicollinearity feature of Xiangjiang River basin and the analysis of 43-year runoff data of the basin,seven indicators were selected for sample prediction including the survey values of runoff,precipitation and evaporation capacity by using the principal component regression method.The analysis shows that by comparison with multiple linear regression,the principal component regression method own smaller errors and more close to the actual situation.
Keywords:multicollinearity  principal component regression  multi-dimensional linear regression  runoff forecasting
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