Estimation of total sediment load concentration obtained by experimental study using artificial neural networks |
| |
Authors: | Emrah Doğan İbrahim Yüksel Özgür Kişi |
| |
Institution: | (1) Faculty of Engineering-Hydraulics Division, Civil Engineering Department, Sakarya University, Sakarya, 54187, Turkey;(2) Technical Education Faculty, Construction Department, Sakarya University, Sakarya, 54187, Turkey;(3) Faculty of Engineering-Hydraulics Division, Civil Engineering Department, Erciyes University, Kayseri, 38039, Turkey |
| |
Abstract: | Estimation of sediment concentration in rivers is very important for water resources projects planning and managements. The
sediment concentration is generally determined from the direct measurement of sediment concentration of river or from sediment
transport equations. Direct measurement is very expensive and cannot be conducted for all river gauge stations. However, sediment
transport equations do not agree with each other and require many detailed data on the flow and sediment characteristics.
The main purpose of the study is to establish an effective model which includes nonlinear relations between dependent (total
sediment load concentration) and independent (bed slope, flow discharge, and sediment particle size) variables. In the present
study, by performing 60 experiments for various independent data, dependent variables were obtained, because of the complexity
of the phenomena, as a soft computing method artificial neural networks (ANNs) which is the powerful tool for input–output
mapping is used. However, ANN model was compared with total sediment transport equations. The results show that ANN model
is found to be significantly superior to total sediment transport equations. |
| |
Keywords: | Artificial neural networks Sediment concentration Sediment transport equations |
本文献已被 SpringerLink 等数据库收录! |
|