Abul Kashem
- Hybrid data-driven approaches to predicting the compressive strength of ultra-high-performance concrete using SHAP and PDP analyses. Dans: Case Studies in Construction Materials, v. 20 (juillet 2024). (2024):
- Compressive strength prediction of sustainable concrete incorporating rice husk ash (RHA) using hybrid machine learning algorithms and parametric analyses. Dans: Case Studies in Construction Materials, v. 20 (juillet 2024). (2024):
- A comparative study of machine learning models for construction costs prediction with natural gradient boosting algorithm and SHAP analysis. Dans: Asian Journal of Civil Engineering. :
- Hybrid machine learning approach to prediction of the compressive and flexural strengths of UHPC and parametric analysis with shapley additive explanations. Dans: Case Studies in Construction Materials, v. 20 (juillet 2024). (2024):
- Synergistic effects of supplementary cementitious materials and compressive strength prediction of concrete using machine learning algorithms with SHAP and PDP analyses. Dans: Case Studies in Construction Materials, v. 20 (juillet 2024). (2024):
- Prediction of high-performance concrete compressive strength using deep learning techniques. Dans: Asian Journal of Civil Engineering, v. 25, n. 1 (juillet 2023). (2023):
- Sustainable of rice husk ash concrete compressive strength prediction utilizing artificial intelligence techniques. Dans: Asian Journal of Civil Engineering, v. 25, n. 2 (octobre 2023). (2023):
- Compressive strength prediction of high-strength concrete using hybrid machine learning approaches by incorporating SHAP analysis. Dans: Asian Journal of Civil Engineering, v. 24, n. 8 (juin 2023). (2023):