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Furqan Farooq
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Predictive modeling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners
F Farooq, W Ahmed, A Akbar, F Aslam, R Alyousef
Journal of Cleaner Production 292, 126032, 2021
2582021
Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms
H Song, A Ahmad, F Farooq, KA Ostrowski, M Maślak, S Czarnecki, ...
Construction and Building Materials 308, 125021, 2021
2152021
A comparative study of random forest and genetic engineering programming for the prediction of compressive strength of high strength concrete (HSC)
F Farooq, M Nasir Amin, K Khan, M Rehan Sadiq, MF Javed, F Aslam, ...
Applied Sciences 10 (20), 7330, 2020
1892020
Prediction of compressive strength of fly ash based concrete using individual and ensemble algorithm
A Ahmad, F Farooq, P Niewiadomski, K Ostrowski, A Akbar, F Aslam, ...
Materials 14 (4), 794, 2021
1682021
Geopolymer concrete as sustainable material: A state of the art review
F Farooq, X Jin, MF Javed, A Akbar, MI Shah, F Aslam, R Alyousef
Construction and Building Materials 306, 124762, 2021
1672021
Applications of gene expression programming for estimating compressive strength of high‐strength concrete
F Aslam, F Farooq, MN Amin, K Khan, A Waheed, A Akbar, MF Javed, ...
Advances in Civil Engineering 2020 (1), 8850535, 2020
1622020
Compressive strength of Fly‐ash‐based Geopolymer concrete by gene expression programming and random Forest
MA Khan, SA Memon, F Farooq, MF Javed, F Aslam, R Alyousef
Advances in Civil Engineering 2021 (1), 6618407, 2021
1572021
Applications of gene expression programming and regression techniques for estimating compressive strength of bagasse ash based concrete
MF Javed, MN Amin, MI Shah, K Khan, B Iftikhar, F Farooq, F Aslam, ...
Crystals 10 (9), 737, 2020
1402020
Compressive strength prediction via gene expression programming (GEP) and artificial neural network (ANN) for concrete containing RCA
A Ahmad, K Chaiyasarn, F Farooq, W Ahmad, S Suparp, F Aslam
Buildings 11 (8), 324, 2021
1312021
Comparative study of supervised machine learning algorithms for predicting the compressive strength of concrete at high temperature
A Ahmad, KA Ostrowski, M Maślak, F Farooq, I Mehmood, A Nafees
Materials 14 (15), 4222, 2021
1212021
Sugarcane bagasse ash-based engineered geopolymer mortar incorporating propylene fibers
A Akbar, F Farooq, M Shafique, F Aslam, R Alyousef, H Alabduljabbar
Journal of Building Engineering 33, 101492, 2021
1132021
Predictive modeling of mechanical properties of silica fume-based green concrete using artificial intelligence approaches: MLPNN, ANFIS, and GEP
A Nafees, MF Javed, S Khan, K Nazir, F Farooq, F Aslam, MA Musarat, ...
Materials 14 (24), 7531, 2021
1022021
New prediction model for the ultimate axial capacity of concrete-filled steel tubes: An evolutionary approach
MF Javed, F Farooq, SA Memon, A Akbar, MA Khan, F Aslam, R Alyousef, ...
Crystals 10 (9), 741, 2020
992020
Geopolymer concrete compressive strength via artificial neural network, adaptive neuro fuzzy interface system, and gene expression programming with K-fold cross validation
MA Khan, A Zafar, F Farooq, MF Javed, R Alyousef, H Alabduljabbar, ...
Frontiers in Materials 8, 621163, 2021
872021
A comparative study for the prediction of the compressive strength of self-compacting concrete modified with fly ash
F Farooq, S Czarnecki, P Niewiadomski, F Aslam, H Alabduljabbar, ...
Materials 14 (17), 4934, 2021
852021
Application of novel machine learning techniques for predicting the surface chloride concentration in concrete containing waste material
A Ahmad, F Farooq, KA Ostrowski, K Śliwa-Wieczorek, S Czarnecki
Materials 14 (9), 2297, 2021
812021
Experimental investigation of hybrid carbon nanotubes and graphite nanoplatelets on rheology, shrinkage, mechanical, and microstructure of SCCM
F Farooq, A Akbar, RA Khushnood, WLB Muhammad, SKU Rehman, ...
Materials 13 (1), 230, 2020
752020
Treatment of pulp and paper industrial effluent using physicochemical process for recycling
K Mehmood, SKU Rehman, J Wang, F Farooq, Q Mahmood, AM Jadoon, ...
Water 11 (11), 2393, 2019
602019
Simulation of depth of wear of eco-friendly concrete using machine learning based computational approaches
MA Khan, F Farooq, MF Javed, A Zafar, KA Ostrowski, F Aslam, ...
Materials 15 (1), 58, 2021
472021
Prediction of compressive strength of sustainable foam concrete using individual and ensemble machine learning approaches
HS Ullah, RA Khushnood, F Farooq, J Ahmad, NI Vatin, DYZ Ewais
Materials 15 (9), 3166, 2022
412022
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Articles 1–20