| contributor author | Mohammad Najafzadeh | |
| contributor author | Gholam-Abbas Barani | |
| contributor author | Masoud Reza Hessami Kermani | |
| date accessioned | 2017-05-08T22:05:51Z | |
| date available | 2017-05-08T22:05:51Z | |
| date copyright | August 2014 | |
| date issued | 2014 | |
| identifier other | 25541610.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/71246 | |
| description abstract | In the present study, the group method of data handling (GMDH) network is applied to predict scour depth below pipelines exposed to waves. The GMDH network is trained using a back-propagation (BP) algorithm. The pipeline scour is modeled as a function of three-dimensionless parameters, including the Keulegan-Carpenter number, the ratio of the initial gap to pipe diameter, and the Shields parameter. The performances of the GMDH network are compared with the adaptive neuro-fuzzy inference system (ANFIS) model, the model tree (MT), and empirical equation. The results indicated that the GMDH network produced a more accurate prediction of scour depth compared with other models. | |
| publisher | American Society of Civil Engineers | |
| title | Estimation of Pipeline Scour due to Waves by GMDH | |
| type | Journal Paper | |
| journal volume | 5 | |
| journal issue | 3 | |
| journal title | Journal of Pipeline Systems Engineering and Practice | |
| identifier doi | 10.1061/(ASCE)PS.1949-1204.0000171 | |
| tree | Journal of Pipeline Systems Engineering and Practice:;2014:;Volume ( 005 ):;issue: 003 | |
| contenttype | Fulltext | |