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Ehsani, M., Ostovari, M., Mansouri, S., Naseri, H., Jahanbakhsh, H., & Nejad, F. M. (2024). Machine learning for predicting concrete carbonation depth: A comparative analysis and a novel feature selection. Construction and Building Materials, 417, 17-17. Lien externe
Jahanbakhsh, H., Moghadas Nejad, F., Khodaii, A., Karimi, M. M., & Naseri, H. (2024). Sustainable Induction-Heatable Cold Patching Using Microwave and Reclaimed Asphalt Pavement. Journal of Materials in Civil Engineering, 36(3), 22 pages. Lien externe
Ghavami, S., Alipour, Z., Naseri, H., Jahanbakhsh, H., & Karimi, M. M. (2023). A New Ensemble Prediction Method for Reclaimed Asphalt Pavement (RAP) Mixtures Containing Different Constituents. Buildings, 13(7), 30 pages. Disponible
Naseri, H., Shokoohi, M., Jahanbakhsh, H., Karimi, M. M., & Waygood, O. (2023). Novel Soft-Computing Approach to Better Predict Flexible Pavement Roughness. Transportation Research Record, 2677(10), 246-259. Lien externe
Naseri, H., Jahanbakhsh, H., Foomajd, A., Galustanian, N., Karimi, M. M., & Waygood, O. (2022). A newly developed hybrid method on pavement maintenance and rehabilitation optimization applying Whale Optimization Algorithm and random forest regression. International Journal of Pavement Engineering, 13 pages. Lien externe
Naseri, H., Hosseini, P., Jahanbakhsh, H., Hosseini, P., & Gandomi, A. H. (2022). A novel evolutionary learning to prepare sustainable concrete mixtures with supplementary cementitious materials. Environment Development and Sustainability, 25(7), 5831-5865. Lien externe
