Radial basis function neural network for modeling rating curves

被引:114
作者
Sudheer, KP [1 ]
Jain, SK
机构
[1] Natl Inst Hydrol, DRC, Kakinada 533003, India
[2] Natl Inst Hydrol, Roorkee 247667, Uttar Pradesh, India
[3] Louisiana State Univ, Dept Civil Engn, Baton Rouge, LA 70803 USA
关键词
neural networks; rating; models; water discharge; gaging stations;
D O I
10.1061/(ASCE)1084-0699(2003)8:3(161)
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The establishment of a rating curve is an important problem in hydrology. Generally, a regression approach is applied to establish the relationship between stage and discharge. However, this approach fails in the cases where hysteresis is present in the data. The aim of the study is to investigate the potential of employing radial basis function (RBF) type neural networks for modeling stage-discharge relationships at gauging stations and to compare different types of networks. The results are promising and suggest that the neural network approach is highly viable. A comparison of the RBF models with backpropagation type neural networks reveals that the former is superior in performance for rating curves exhibiting hysteresis.
引用
收藏
页码:161 / 164
页数:4
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