| contributor author | Ata Aghaei | |
| contributor author | Araei | |
| date accessioned | 2017-05-08T21:45:56Z | |
| date available | 2017-05-08T21:45:56Z | |
| date copyright | June 2014 | |
| date issued | 2014 | |
| identifier other | %28asce%29gm%2E1943-5622%2E0000337.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/61723 | |
| description abstract | In this paper, the feasibility of developing and using artificial neural networks (ANNs) for modeling the monotonic behaviors of various angular and rounded rockfill materials is investigated. The database used for development of the ANN models is comprised of a series of 82 large-scale, drained triaxial tests. The deviator stress-volumetric strain versus axial strain behaviors were first simulated by using ANNs. A feedback model using multilayer perceptrons for predicting drained behavior of rockfill materials was developed in the | |
| publisher | American Society of Civil Engineers | |
| title | Artificial Neural Networks for Modeling Drained Monotonic Behavior of Rockfill Materials | |
| type | Journal Paper | |
| journal volume | 14 | |
| journal issue | 3 | |
| journal title | International Journal of Geomechanics | |
| identifier doi | 10.1061/(ASCE)GM.1943-5622.0000323 | |
| tree | International Journal of Geomechanics:;2014:;Volume ( 014 ):;issue: 003 | |
| contenttype | Fulltext | |
