摘要
为提高流域中长期径流预测效果,提出径流综合指数构建、因子筛选和改进深度信念网络模型相结合的预测方法。首先研究不同水文站点(细粒度)月平均径流的一致性,构造流域径流综合指数(粗粒度),在较宏观层面研究流域水情丰枯变化;接着采用基于信息熵的因子筛选方法,获得影响流域水情丰枯变化的关键因子集,形成深度学习的输入;然后利用改进的深度信念网络(IDBN)模型进行预测。以雅砻江流域为例,将所建模型与多元线性回归、自回归移动平均、反向传播(BP)神经网络、支持向量机和传统深度信念网络等预测模型进行对比分析。结果表明:所提方法具有较好的实用性,且IDBN模型具有更好的预测速度和精度。研究结果可为流域中长期径流变化趋势预测提供参考。
To improve the mid-and long-term runoff forecasting of a watershed,this paper develops a new method integrating a comprehensive runoff index,factor reduction,and an improved deep belief networks model.First,we examine the consistency of runoff at different hydrological stations and construct a comprehensive runoff index to characterize the abundance and drought of runoff in the watershed.And we apply a partial mutual information approach to select key factors from the multiple factors,and the selected key factors are taken as inputs of deep learning.Then,an improved deep belief networks(IDBN)model is developed for mid-and long-term runoff forecasting.In a case study of Yalong River basin,this model is compared with several state-of-the-art forecasting models:multivariable linear regression(MLR),autoregressive integrated moving average(ARIMA)model,backpropagation neural networks(BPNN),support vector machines(SVM),and typical deep belief networks models.Results demonstrate our method can significantly reduce computational cost and improve forecasting accuracy,thus helping the mid-and long-term runoff forecasting of watersheds.
作者
岳兆新
艾萍
熊传圣
宋艳红
洪敏
于家瑞
YUE Zhaoxin;AI Ping;XIONG Chuansheng;SONG Yanhong;HONG Min;YU Jiarui(College of Computer and Information Engineering,Hohai University,Nanjing 211100;College of Hydrology and Water Resources,Hohai University,Nanjing 210098)
出处
《水力发电学报》
EI
CSCD
北大核心
2020年第10期33-46,共14页
Journal of Hydroelectric Engineering
基金
国家自然科学基金重大研究计划重点支持项目(91846203)
中央高校基本科研业务费专项资金资助(2018B610X14)
江苏省研究生科研与实践创新计划项目(KYCX18_0583)
关键词
水文预报
中长期径流预测
径流综合指数
偏互信息法
深度信念网络
hydrological forecasting
mid-and long-term runoff forecasting
comprehensive runoff index
partial mutual information
deep belief networks
作者简介
岳兆新(1985—),男,博士生.E-mail:yzx10000@163.com;通信作者:艾萍(1961—),男,教授.E-mail:aip@hhu.edu.cn
