水资源与水工程学报2017，Vol.28Issue(1)：40-44,5.DOI:10.11705/j.issn.1672-643X.2017.01.07
新安江模型和改进BP神经网络模型在闽江水文预报中的应用
Application of Xin'anjiang model and the improved BP neural network model in hydrological forecasting of the Min River
摘要
Abstract
Accurate hydrological forecasting is an important non-engineering measure in flood disaster relief.Hydrologic models are the most useful tool for hydrological forecasting.The BP neural network model was improved by introducing LM algorithm,together with the Xin'anjiang Model,their applications for daily flow simulating and forecasting to the Futun River of the Min River were compared.The results showed that,both hydrologic models reached the accuracy requirements of hydrological forecasting with over 90％ of hydrological forcasting qualified rate.The Xin'anjiang model performed better for the wet years while the improved BP model was better in simulating accuracy than the Xin'anjiang model.Both models were applicable to the hydrological forecasting of Min River.关键词
新安江模型/参数率定/BP神经网络模型/LM算法/洪水预报Key words
Xin'anjiang model/parameter calibration/BP neural network model/LM algorithm/flood forecast分类
建筑与水利引用本文复制引用
刘佩瑶,郝振纯,王国庆,赵思远,王乐扬..新安江模型和改进BP神经网络模型在闽江水文预报中的应用[J].水资源与水工程学报,2017,28(1):40-44,5.基金项目
“十三五”国家重点研发计划项目(2016YFA0601501、2016YFA0601601) （2016YFA0601501、2016YFA0601601）
国家自然科学基金项目(41330854、41371063、51679145) （41330854、41371063、51679145）
