水资源与水工程学报2017，Vol.28Issue(3)：123-126,133,5.DOI:10.11705/j.issn.1672-643X.2017.03.23
多元线性回归与BP神经网络模型在次洪量预测中的对比研究
Comparative study on multivariate linear regression and BP neural network model in the prediction of flood volume
摘要
Abstract
Aiming at the problem of flood volume forecast in semi-arid area, we selected 15 flood data of the Caoping hydrological station in Chabagou watershed from 1980 to 2010.According to the measured single storm, flood control data in Chabagou watershed, considering the warp land dam area, storm rainfall, rainfall center, antecedent rainfall and others factors, combined with SPSS and MATLAB software, multivariate linear regression model and BP neural network model for the prediction of flood volume were built.The prediction results of the two models show that multivariate linear regression model and BP neural network model can be better applied to flood volume prediction, and the BP neural network model is superior to multivariate linear regression model.Research result can provide decision-making basis for dam safety in the flood season.关键词
淤地坝/次洪量预报/多元线性回归/BP神经网络Key words
warp land dam/flood volume prediction/multiple linear regression/BP neural network分类
建筑与水利引用本文复制引用
冯鑫伟,黄领梅,沈冰..多元线性回归与BP神经网络模型在次洪量预测中的对比研究[J].水资源与水工程学报,2017,28(3):123-126,133,5.基金项目
国家自然科学基金项目(51679184) （51679184）
陕西省水利厅项目(2016slkj-12) （2016slkj-12）
