Compressive strength of fly‐ash‐based geopolymer concrete by gene expression programming and random forest

MA Khan, SA Memon, F Farooq… - Advances in Civil …, 2021 - Wiley Online Library
Fly ash (FA) is a residual from thermal industries that has been effectively utilized in the
production of FA‐based geopolymer concrete (FGPC). To avoid time‐consuming and costly …

[HTML][HTML] A review of recent developments and advances in eco-friendly geopolymer concrete

L Imtiaz, SKU Rehman, S Ali Memon, M Khizar Khan… - Applied sciences, 2020 - mdpi.com
The emission of CO2 and energy requirement in the production of Ordinary Portland Cement
(OPC) causes the continuous depletion of ozone layer and global warming. The introduction …

[HTML][HTML] Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms

H Song, A Ahmad, F Farooq, KA Ostrowski… - … and Building Materials, 2021 - Elsevier
The cementitious composites have different properties in the changing environment. Thus,
knowing their mechanical properties is very important for safety reasons. The most important …

Prediction of compressive strength of fly ash based concrete using individual and ensemble algorithm

A Ahmad, F Farooq, P Niewiadomski, K Ostrowski… - Materials, 2021 - mdpi.com
Machine learning techniques are widely used algorithms for predicting the mechanical
properties of concrete. This study is based on the comparison of algorithms between …

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… - Applied Sciences, 2020 - mdpi.com
Supervised machine learning and its algorithm is an emerging trend for the prediction of
mechanical properties of concrete. This study uses an ensemble random forest (RF) and …

[HTML][HTML] 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… - Materials, 2021 - mdpi.com
High temperature severely affects the nature of the ingredients used to produce concrete,
which in turn reduces the strength properties of the concrete. It is a difficult and time …

Geopolymer concrete compressive strength via artificial neural network, adaptive neuro fuzzy interface system, and gene expression programming with K-fold cross …

MA Khan, A Zafar, F Farooq, MF Javed… - Frontiers in …, 2021 - frontiersin.org
The ultrafine fly ash (FA) is a hazardous material collected from coal productions, which has
been proficiently employed for the manufacturing of geopolymer concrete (GPC). In this …

[HTML][HTML] Forecasting the strength of graphene nanoparticles-reinforced cementitious composites using ensemble learning algorithms

M Khan, W Anwar, M Rasheed, T Najeh, Y Gamil… - Results in …, 2024 - Elsevier
Contemporary infrastructure requires structural elements with enhanced mechanical
strength and durability. Integrating nanomaterials into concrete is a promising solution to …

[HTML][HTML] Modeling of mechanical properties of silica fume-based green concrete using machine learning techniques

A Nafees, MN Amin, K Khan, K Nazir, M Ali, MF Javed… - Polymers, 2021 - mdpi.com
Silica fume (SF) is a frequently used mineral admixture in producing sustainable concrete in
the construction sector. Incorporating SF as a partial substitution of cement in concrete has …

Applications of gene expression programming for estimating compressive strength of high‐strength concrete

F Aslam, F Farooq, MN Amin, K Khan… - Advances in Civil …, 2020 - Wiley Online Library
The experimental design of high‐strength concrete (HSC) requires deep analysis to get the
target strength. In this study, machine learning approaches and artificial intelligence python …