Predictive modeling of compressive strength in silica fume‐modified self‐compacted concrete: A soft computing approach
Payam Ismael Abdulrahman(Tishk International University), Parveen Sihag(Chandigarh University), Rawaz Kurda(Duhok Polytechnic University), Ahmed Salih Mohammed(University of Sulaimani), Sirwan Khuthur Malla(Salahaddin University-Erbil), Panagiotis G. Asteris(School of Pedagogical and Technological Education), Dilshad Kakasor Ismael Jaf(Salahaddin University-Erbil)
Cited by 8
Related Papers
Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models
|Cement and Concrete Research|2021|668
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
|Neural Computing and Applications|2020|456
Concrete compressive strength using artificial neural networks
|Neural Computing and Applications|2019|432
A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model
|Engineering With Computers|2020|349
Mathematical Macromodeling of Infilled Frames: State of the Art
|Journal of Structural Engineering|2011|329