| Comparative analysis of GMDH neural network based on genetic algorithm and particle swarm optimization in stable channel design S Shaghaghi, H Bonakdari, A Gholami, I Ebtehaj, M Zeinolabedini Applied Mathematics and Computation 313, 271-286, 2017 | 108 | 2017 |
| Developing an expert group method of data handling system for predicting the geometry of a stable channel with a gravel bed A Gholami, H Bonakdari, I Ebtehaj, S Shaghaghi, F Khoshbin Earth Surface Processes and Landforms 42 (10), 1460-1471, 2017 | 59 | 2017 |
| Predicting the geometry of regime rivers using M5 model tree, multivariate adaptive regression splines and least square support vector regression methods S Shaghaghi, H Bonakdari, A Gholami, O Kisi, A Binns, B Gharabaghi International Journal of River Basin Management 17 (3), 333-352, 2019 | 34 | 2019 |
| Stable alluvial channel design using evolutionary neural networks S Shaghaghi, H Bonakdari, A Gholami, O Kisi, J Shiri, AD Binns, ... Journal of Hydrology 566, 770-782, 2018 | 24 | 2018 |
| An optimal Adaptive Neural Fuzzy Inference System (ANFIS) model and regression relations to predict stable channel geometry in rivers gravel bed A Gholami, H Bonakdari, I Ebtehaj, S Shaghaghi 10th International River Engineering Conference, 2016 | 1 | 2016 |
| Application of Artificial Neural Network (ANN) and Support Vector Machine (SVM) in estimation of stable channel geometry S Shaghaghi, H Bonakdari, A Gholami, I Ebtehaj 10th International River Engineering Conference, 2016 | | 2016 |
