Prediction of suspended sediment in river using fuzzy logic and multilinear regression approaches

被引：37

作者：

Demirci, Mustafa ^{[1
]}

Baltaci, Ahmet ^{[1
]}

机构：

[1] Mustafa Kemal Univ, Fac Engn, Dept Civil Engn, Hydraul Div, TR-31040 Iskenderun, Hatay, Turkey

来源：

NEURAL COMPUTING & APPLICATIONS | 2013年 / 23卷

关键词：

Suspended sediment; Forecasting; Fuzzy logic; Sediment rating curve; Multilinear regression; TRANSPORT; DISCHARGE; CURVES;

D O I：

10.1007/s00521-012-1280-z

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Prediction of sediment concentration in a river is very important for many water resource projects. Conventional sediment rating curves (SRC), however, are not able to provide sufficiently accurate results. In this paper, a fuzzy logic approach is proposed to estimate suspended sediment concentration from streamflow. A comparison was performed between fuzzy logic (FL), SRC and multilinear regression models. It was based on a 5-year period of continuous streamflow, suspended sediment concentration and mean water temperature data of Sacremento Freeport Station operated by the United States Geological Survey. Based on the comparison of the results, it is found that the FL model gives better estimates than the other techniques.

引用

页码：S145 / S151

页数：7

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