摘要
提出了适用于河道洪水预报的神经网络模型,应用实测水文资料与河道洪水演算的马斯京干法进行了比较,得出:神经网络模型几乎没有能力进行河道洪水的连续模拟;对于线性河道系统的实时洪水预报,马法优于神经网络模型;对于非线性河道的实时洪水预报,两者相差不大,神经网络模型略优一些.
A channel flood routing model of Artificial Neural Network (ANN) is put forward in the paper and compared with the Muskingum method by means of the observed hydrological data. Some useful suggestions are presented.
出处
《河海大学学报(自然科学版)》
CAS
CSCD
1997年第5期7-12,共6页
Journal of Hohai University(Natural Sciences)
关键词
水文模拟
神经网络
洪水演算
河道
hydrological modelling
artificial neural network
flood routing
Muskingum method