Stream Flow Modeling of River Swat Using Regression and Artificial Neural Networks (ANNs) Techniques

被引：1

作者：

Daud, Suleman ^{[1
]}

Shahzada, Khan ^{[2
]}

Tufail, M. ^{[3
]}

Fahad, M. ^{[3
]}

机构：

[1] Govt Khyber, Gomal Zam Dam Irrigat Div, Pukhtoonkhwa, Pakistan

[2] NWFP Univ Engn & Technol Peshawar, Dept Civil Engn, Peshawar, Pakistan

[3] SUNY Buffalo, Buffalo, NY 14228 USA

来源：

ADVANCES IN CIVIL ENGINEERING, PTS 1-6 | 2011年 / 255-260卷

关键词：

Forecasting; Artificial Neural Networks; Regression; Floods;

D O I：

10.4028/www.scientific.net/AMR.255-260.679

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This paper presents the utility of Artificial Neural Networks and Regression analysis for the stream flow modeling in Swat River at five discharge gauge station. As an appropriate intelligent model is identified, Artificial Neural Networks (ANNs) is evaluated by comparing it to regression analysis and the available field data. ANNs namely feed forward back propagation neural network (FFBPNN) and regression analysis are introduced and implemented. The research study successfully compared the performance of the ANN and regression models that validated the utility of the two modeling techniques as effective applications to stream flow forecasting.

引用

页码：679 / +

页数：2