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Furqan Farooq

Predictive modeling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners
2021 · Furqan Farooq, Wisal Ahmed, et al. · Journal of Cleaner Production · 436
Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms
2021 · Hongwei Song, Ayaz Ahmad, et al. · Construction and Building Materials · 407
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Geopolymer concrete as sustainable material: A state of the art review
2021 · Furqan Farooq, Xin Jin, et al. · Construction and Building Materials · 367
A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)
2020 · Furqan Farooq, Muhammad Nasir Amin, et al. · Applied Sciences · 295
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Prediction of Compressive Strength of Fly Ash Based Concrete Using Individual and Ensemble Algorithm
2021 · Ayaz Ahmad, Furqan Farooq, et al. · Materials · 275
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Comparative Study of Supervised Machine Learning Algorithms for Predicting the Compressive Strength of Concrete at High Temperature
2021 · Ayaz Ahmad, Krzysztof Adam Ostrowski, et al. · Materials · 240
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Applications of Gene Expression Programming for Estimating Compressive Strength of High‐Strength Concrete
2020 · Fahid Aslam, Furqan Farooq, et al. · Advances in Civil Engineering · 223
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Compressive Strength of Fly‐Ash‐Based Geopolymer Concrete by Gene Expression Programming and Random Forest
2021 · Mohsin Ali Khan, Shazim Ali Memon, et al. · Advances in Civil Engineering · 217
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Compressive Strength Prediction via Gene Expression Programming (GEP) and Artificial Neural Network (ANN) for Concrete Containing RCA
2021 · Ayaz Ahmad, Krisada Chaiyasarn, et al. · Buildings · 204
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Applications of Gene Expression Programming and Regression Techniques for Estimating Compressive Strength of Bagasse Ash based Concrete
2020 · Muhammad Faisal Javed, Muhammad Nasir Amin, et al. · Crystals · 171
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Predictive Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Artificial Intelligence Approaches: MLPNN, ANFIS, and GEP
2021 · Afnan Nafees, Muhammad Javed, et al. · Materials · 167
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Geopolymer Concrete Compressive Strength via Artificial Neural Network, Adaptive Neuro Fuzzy Interface System, and Gene Expression Programming With K-Fold Cross Validation
2021 · Mohsin Ali Khan, Adeel Zafar, et al. · Frontiers in Materials · 157
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Sugarcane bagasse ash-based engineered geopolymer mortar incorporating propylene fibers
2020 · Arslan Akbar, Furqan Farooq, et al. · Journal of Building Engineering · 147
A Comparative Study for the Prediction of the Compressive Strength of Self-Compacting Concrete Modified with Fly Ash
2021 · Furqan Farooq, Slawomir Czarnecki, et al. · Materials · 142
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Application of Novel Machine Learning Techniques for Predicting the Surface Chloride Concentration in Concrete Containing Waste Material
2021 · Ayaz Ahmad, Furqan Farooq, et al. · Materials · 133
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New Prediction Model for the Ultimate Axial Capacity of Concrete-Filled Steel Tubes: An Evolutionary Approach
2020 · Muhammad Faisal Javed, Furqan Farooq, et al. · Crystals · 127
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Prediction of Compressive Strength of Sustainable Foam Concrete Using Individual and Ensemble Machine Learning Approaches
2022 · Haji Ullah, Rao Khushnood, et al. · Materials · 85
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Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches
2021 · Mohsin Ali Khan, Furqan Farooq, et al. · Materials · 85
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Experimental Investigation of Hybrid Carbon Nanotubes and Graphite Nanoplatelets on Rheology, Shrinkage, Mechanical, and Microstructure of SCCM
2020 · Furqan Farooq, Arslan Akbar, et al. · Materials · 79
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Predictive modelling of sustainable lightweight foamed concrete using machine learning novel approach
2022 · Haji Sami Ullah, Rao Arsalan Khushnood, et al. · Journal of Building Engineering · 77
Prediction of sustainable concrete utilizing rice husk ash (RHA) as supplementary cementitious material (SCM): Optimization and hyper-tuning
2023 · Muhammad Nasir Amin, Kaffayatullah Khan, et al. · Journal of Materials Research and Technology · 62
A comparative study on performance evaluation of hybrid GNPs/CNTs in conventional and self-compacting mortar
2020 · Furqan Farooq, Sardar Kashif Ur Rahman, et al. · Alexandria Engineering Journal · 48
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Forecasting the strength of graphene nanoparticles-reinforced cementitious composites using ensemble learning algorithms
2024 · Majid Khan, Roz-Ud-Din Nassar, et al. · Results in Engineering · 47
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A novel approach in forecasting compressive strength of concrete with carbon nanotubes as nanomaterials
2023 · Hongbo Jiao, Yonggang Wang, et al. · Materials Today Communications · 47
Micro-cracking pattern recognition of hybrid CNTs/GNPs cement pastes under three-point bending loading using acoustic emission technique
2021 · Jie Xu, Shahzad Ashraf, et al. · Journal of Building Engineering · 47
Works count: 44
Citation count: 4,747
H-index: 32
I10-index: 39
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