| Development of a Support Vector Machine (SVM) and a Classification and Regression Tree (CART) to Predict the Shear Strength of Sand Rubber Mixtures A Baghbani, F Daghistani, HA Naga, S Costa Proceedings of the 8th International Symposium on Geotechnical Safety and …, 2022 | 16 | 2022 |
| AI-Based Prediction of Strength and Tensile Properties of Expansive Soil Stabilized with Recycled Ash and Natural Fibers A Baghbani, F Daghistani, K Kiany, MM Shalchiyan EasyChair: Manchester, UK, 2023 | 14 | 2023 |
| Predicting the Strength of Recycled Glass Powder-Based Geopolymers for Improving Mechanical Behavior of Clay Soils Using Artificial Intelligence A Baghbani, F Daghistani, H Baghbani, K Kiany EasyChair: Manchester, UK, 2023 | 13 | 2023 |
| Artificial Intelligence-Based Prediction of Geotechnical Impacts of Polyethylene Bottles and Polypropylene on Clayey Soil A Baghbani, F Daghistani, H Baghbani, K Kiany, JB Bazaz EasyChair: Manchester, UK, 2023 | 12 | 2023 |
| Internal Friction Angle of Cohesionless Binary Mixture Sand–Granular Rubber Using Experimental Study and Machine Learning F Daghistani, A Baghbani, H Abuel Naga, RS Faradonbeh Geosciences 13 (7), 197, 2023 | 9 | 2023 |
| Evaluating the Influence of Sand Particle Morphology on Shear Strength: A Comparison of Experimental and Machine Learning Approaches F Daghistani, H Abuel-Naga Applied Sciences 13 (14), 8160, 2023 | 7 | 2023 |
| Shear strength characteristics of binary mixture sand-carpet fibre using experimental study and machine learning F Daghistani, A Baghbani, H Abuel Naga International Journal of Geotechnical Engineering, 2023 | 2 | 2023 |
| Shear Strength Characteristics of Sand-Particulate Rubber Mixture F Daghistani, HA Naga International Journal of Geotechnical and Geological Engineering 17 (3), 36-41, 2023 | 2 | 2023 |
| Predicting the Strength Performance of Hydrated-Lime Activated Rice Husk Ash-Treated Soil Using Two Grey-Box Machine Learning Models A Baghbani, A Soltani, K Kiany, F Daghistani Geotechnics 3 (3), 894-920, 2023 | 1 | 2023 |
| Advancements in Understanding Interface Friction: A Combined Experimental and Machine Learning Approach Using Multiple Linear and Random Forest Regressions F Daghistani, H Abuel-Naga Geotechnics 4 (1), 109-126, 2024 | | 2024 |
| Effects of Dry Density and Moisture Content on the Kaolin–Brass Interfacial Shear Adhesion R Almasoudi, H Abuel-Naga, F Daghistani Applied Sciences 13 (20), 11191, 2023 | | 2023 |
| The prediction of soil cracking caused by desiccation using artificial intelligence and statistical analysis BT A Baghbani, MJ Yaghoubi, F Daghistani, S Costa Proceedings 10th European Conference on Numerical Methods in Geotechnical …, 2023 | | 2023 |
| Improving Soil Liquefaction Potential Evaluation through AI-Based Prediction of SPT Values: A Comparative Study JBB A Baghbani, F Daghistani, MM Shalchiyan, S Costa, H Baghbani, R Shirani ... Proceedings 10th European Conference on Numerical Methods in Geotechnical …, 2023 | | 2023 |
Abolfazl (Nima) BaghbaniPhD candidate in Geotechnical engineering, Deakin University, Melbourne, AustraliaVerified email at deakin.edu.au
