人民珠江2025，Vol.46Issue(6)：68-74,7.DOI:10.3969/j.issn.1001-9235.2025.06.008
崇阳溪流域PRBP神经网络洪水预报模型研究
Research on PRBP Neural Network Flood Forecasting Model in Chongyang River Basin
摘要
Abstract
The Poak-Ribiére conjugate gradient back propagation algorithm(PRBP)of numerical optimization technology was used,and 21 rainstorm and flood processes from 1997 to 2022 in the upper reaches of Chongyang River basin were studied.The rainfall volume of six rainfall stations in the upper reaches of Chongyang River basin and the previous discharge of Wuyishan Hydrological Station were regarded as input,and its corresponding discharge was regarded as output;the number of hidden layer units was determined by trial calculation,and then PRBP neural network flood forecasting model of Chongyangxi River Basin was established.The remaining eight floods were used to test and validate the model.The results show that compared with that of the conventional BP neural network model,the convergence speed of the model is faster,and the calculation speed is obviously improved;the deterministic coefficient of the model is greater than 0.87,and the relative error of peak flow of six floods is within 10%.The forecasting accuracy meets the requirements,which can provide a basis for the flood control department to forecast the flood.关键词
PR共轭梯度法/BP神经网络/洪水预报/崇阳溪流域Key words
PR conjugate gradient method/BP neural network/flood forecasting/Chongyang River Basin分类
水利科学引用本文复制引用
司琪,金保明,卢旺铭,陈朝清..崇阳溪流域PRBP神经网络洪水预报模型研究[J].人民珠江,2025,46(6):68-74,7.基金项目
福建省自然科学基金项目(2023J01405) （2023J01405）
福建省水利科技项目(MSK202408) （MSK202408）
