| contributor author | M. R. Mustafa | |
| contributor author | R. B. Rezaur | |
| contributor author | S. Saiedi | |
| contributor author | H. Rahardjo | |
| contributor author | M. H. Isa | |
| date accessioned | 2017-05-08T21:49:27Z | |
| date available | 2017-05-08T21:49:27Z | |
| date copyright | January 2013 | |
| date issued | 2013 | |
| identifier other | %28asce%29he%2E1943-5584%2E0000620.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/63491 | |
| description abstract | Knowledge of pore-water pressure responses to rainfall is vital in slope failure and slope hydrological studies. The performance of four artificial neural network (ANN) training algorithms was evaluated to identify the training algorithm appropriate for modeling the dynamics of soil pore-water pressure responses to rainfall patterns using multilayer perceptron (MLP) ANN. The ANN model comprised eight neurons in the input layer, four neurons in the hidden layer, and a single neuron in the output layer representing an | |
| publisher | American Society of Civil Engineers | |
| title | Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall | |
| type | Journal Paper | |
| journal volume | 18 | |
| journal issue | 1 | |
| journal title | Journal of Hydrologic Engineering | |
| identifier doi | 10.1061/(ASCE)HE.1943-5584.0000599 | |
| tree | Journal of Hydrologic Engineering:;2013:;Volume ( 018 ):;issue: 001 | |
| contenttype | Fulltext | |