Volume 23, Issue 4 (Special Issue of Flood and Soil Erosion, Winter 2019)
jwss 2019, 23(4): 315-329 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Pourmirza M, Kamanbedast A. Investigation of Local Scour Factors under Pipelines Using Artificial Neural Network Algorithms. jwss 2019; 23 (4) :315-329
URL: http://jstnar.iut.ac.ir/article-1-3560-en.html
URL: http://jstnar.iut.ac.ir/article-1-3560-en.html
1. Department of Civil Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran. , mohammadp2787@gmail.com
Abstract: (4617 Views)
Occurrence of local scour is one of the most significant causes of damage to the pipes. Therefore, safe and economical design of pipes in the flow path requires a good estimate. In this study, based on the important and effective parameters in the scouring phenomenon, in order to develop educational patterns according to the data obtained in the laboratory of Ahvaz Islamic Azad University, models based on artificial neural networks were created with the NeuroSolution5 software. MLP, GFF and RBF were the models used in this study; after comparing, MLP was selected as the basis for our study. Finally, the effect of each parameter on scouring was determined using the artificial neural networks technique, based on which the shields parameter with a very high effect (more than 95 percent) was determined as one of the most effective causes of the local scour.
Keywords: Scour, Artificial neural network, NeuroSolution5 software, Multilayer Perceptron Model (MLP), Shields Parameter
Type of Study: Research |
Subject:
Ggeneral
Received: 2017/08/19 | Accepted: 2018/08/11 | Published: 2019/12/31
Received: 2017/08/19 | Accepted: 2018/08/11 | Published: 2019/12/31
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
