水利水电技术2013，Vol.44Issue(7)：5-9,5.
基于近邻估计的年径流预测动态联系数回归模型
Nearest neighbor estimate based dynamic connection number regression model for predicting annual runoff
摘要
Abstract
The set pair analysis theory provides a new way to identify the uncertain system.The connection number regression model for prediction established in accordance with the set pair analysis theory can significantly improve the prediction accuracy of the regression model.For the dynamics of the structure of the predictive factor,the nearest neighbor estimate is to be adopted for estimating that the predictive factors within a prediction are to be strong or weak through the calculation of the variation coefficients of all the predictive factors,moreover,the strong factors with large predicting function are dynamically selected to eliminate the negative effect from the weak factors on the prediction,thus the dynamics of the structure of the predictive factor is better reflected.On the basis of this,the nearest neighbor estimate based dynamic connection number regression model for predicting annual runoff(NNE-DCNR) is established.The result shows that the predicting accuracy is to be significantly enhanced in comparison with the conventional predicting method,if NNE-DCNR is utilized for predicting the annual runoff,and then it has a high value of popularization and application in the prediction of hydrology and water resources.关键词
年径流预测/近邻估计/回归模型/集对分析/联系数/变异系数Key words
prediction of annual runoff/ nearest neighbor estimate/ regression model/ set pair analysis/ connection number/coefficient of variation分类
天文与地球科学引用本文复制引用
蒋尚明,金菊良,袁先江,汤广民,于凤存..基于近邻估计的年径流预测动态联系数回归模型[J].水利水电技术,2013,44(7):5-9,5.基金项目
水利部公益性行业科研专项(200901077,200901026) （200901077,200901026）
国家自然科学基金项目(51079037,51209001). （51079037,51209001）
