Estimation of strength, rheological parameters, and impact of raw constituents of alkali-activated mortar using machine learning and SHapely Additive exPlanations …

S Nazar, J Yang, XE Wang, K Khan, MN Amin… - … and Building Materials, 2023 - Elsevier
One-part alkali-activated material (AAM) is a new eco-friendly developed low-carbon binder
that utilizes alkaline activators in solid form. This study deals with the experimental synthesis …

[HTML][HTML] Investigating the feasibility of using waste eggshells in cement-based materials for sustainable construction

K Khan, W Ahmad, MN Amin, AF Deifalla - Journal of Materials Research …, 2023 - Elsevier
To investigate the effect of eggshell powder on the water-absorption capacity of cement
mortar, this research employed experimental testing followed by machine learning (ML) …

Interpretable machine learning framework to predict the glass transition temperature of polymers

MJ Uddin, J Fan - Polymers, 2024 - mdpi.com
The glass transition temperature of polymers is a key parameter in meeting the application
requirements for energy absorption. Previous studies have provided some data from slow …

[HTML][HTML] Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques

MN Amin, W Ahmad, K Khan, AF Deifalla - Case Studies in Construction …, 2023 - Elsevier
This research intended to increase the understanding of using modern machine intelligence
techniques, including multi-expression programming (MEP) and gene expression …

[HTML][HTML] A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive …

X Zheng, Y **e, X Yang, MN Amin, S Nazar… - Journal of Materials …, 2023 - Elsevier
This research used gene expression programming (GEP) and multi expression
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …

[HTML][HTML] Testing and modeling methods to experiment the flexural performance of cement mortar modified with eggshell powder

MN Amin, W Ahmad, K Khan, MN Al-Hashem… - Case Studies in …, 2023 - Elsevier
Sustainable development might be promoted if waste eggshells are used in cement-based
materials (CBMs) by decreasing waste disposal problems, CO 2 emissions, and material …

Development of compressive strength prediction platform for concrete materials based on machine learning techniques

K Liu, L Zhang, W Wang, G Zhang, L Xu, D Fan… - Journal of Building …, 2023 - Elsevier
With the continuous development of artificial intelligence, machine learning (ML), as an
important branch, is used to promote the digitalization of concrete. Considering that the …

Predictive modelling for the acid resistance of cement-based composites modified with eggshell and glass waste for sustainable and resilient building materials

Z Chen, MN Amin, B Iftikhar, W Ahmad… - Journal of Building …, 2023 - Elsevier
The increasing demand for cement-based composites (CBCs) due to the advancement of
infrastructure causes the exhaustion of natural materials and environmental pollution. Also …

A novel data driven approach for combating energy theft in urbanized smart grids using artificial intelligence

N Shahzadi, N Javaid, M Akbar… - Expert Systems with …, 2024 - Elsevier
Electricity Theft (ET) causes monetary losses for power utilities in the energy sector. It occurs
when electricity is consumed without being billed. Several methods are available for …

Comprehensible machine-learning-based models for the pre-emptive diagnosis of multiple sclerosis using clinical data: a retrospective study in the eastern province …

SO Olatunji, N Alsheikh, L Alnajrani, A Alanazy… - International Journal of …, 2023 - mdpi.com
Multiple Sclerosis (MS) is characterized by chronic deterioration of the nervous system,
mainly the brain and the spinal cord. An individual with MS develops the condition when the …