Application of artificial neural networks for river regime

被引：0

作者：

Bui, M. D. ^{[1
]}

Huber, D. ^{[1
]}

Kaveh, K. ^{[1
]}

da Silva, A. M. E. ^{[2
]}

Rutschmann, P. ^{[1
]}

机构：

[1] Tech Univ Munich, Inst Hydraul & Water Resources Engn, Munich, Germany

[2] Queens Univ, Dept Civil Engn, Kingston, ON, Canada

来源：

RIVER FLOW 2016 | 2016年

关键词：

D O I：

暂无

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Predicting the geometric characteristics of a regime channel is of utmost importance in the context of river engineering and management, as regime channels require minimum protection and minimum expenses for their maintenance. There are numerous empirical and analytical methods to predict these geometric characteristics. This paper develops and tests an Artificial Neural Network (ANN) as a model to forecast the river regime characteristics. ANN performance is compared against the Thermodynamic Entropy Theory of Yalin and da Silva (2001) and the Stability Theory of Julien and Wargadalam (1995). An improvement in the results of the ANN model has been achieved by distinguishing the input variables into sand and gravel bed materials as well as different discharge groups.

引用

页码：154 / 160

页数：7

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