Majid Khan 
- (2024): Estimating compressive strength of concrete containing rice husk ash using interpretable machine learning-based models. In: Case Studies in Construction Materials, v. 20 (Juli 2024).
- (2024): Predictive modeling for compressive strength of 3D printed fiber-reinforced concrete using machine learning algorithms. In: Case Studies in Construction Materials, v. 20 (Juli 2024).
- (2024): Predictive modeling for depth of wear of concrete modified with fly ash: A comparative analysis of genetic programming-based algorithms. In: Case Studies in Construction Materials, v. 20 (Juli 2024).
- (2024): Application of metaheuristic optimization algorithms in predicting the compressive strength of 3D-printed fiber-reinforced concrete. In: Developments in the Built Environment, v. 17 (März 2024).
- (2023): Forecasting the Strength Characteristics of Concrete incorporating Waste Foundry Sand using advance machine algorithms including deep learning. In: Case Studies in Construction Materials, v. 19 (Dezember 2023).
- (2023): Machine learning-driven predictive models for compressive strength of steel fiber reinforced concrete subjected to high temperatures. In: Case Studies in Construction Materials, v. 19 (Dezember 2023).
- (2023): Predicting ultra-high-performance concrete compressive strength using gene expression programming method. In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2022): Space cooling achievement by using lower electricity in hot months through introducing PCM-enhanced buildings. In: Journal of Building Engineering, v. 53 (August 2022).
- (2022): Per- and Polyfluoroalkyl Substances Presence, Pathways, and Cycling through Drinking Water and Wastewater Treatment. In: Journal of Environmental Engineering (ASCE), v. 148, n. 1 (Januar 2022).
Structurae kooperiert mit
