State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting

J Zhou, Y Zhang, Y Qiu - Artificial Intelligence Review, 2024 - Springer
The technological difficulties related with blasting operations have become increasingly
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …

Innovative modeling techniques including MEP, ANN and FQ to forecast the compressive strength of geopolymer concrete modified with nanoparticles

HU Ahmed, AS Mohammed, RH Faraj… - Neural Computing and …, 2023 - Springer
The use of nano-materials to improve the engineering properties of different types of
concrete composites including geopolymer concrete (GPC) has recently gained popularity …

A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement

M Shariati, MS Mafipour, B Ghahremani… - Engineering with …, 2022 - Springer
Compressive strength of concrete is one of the most determinant parameters in the design of
engineering structures. This parameter is generally determined by conducting several tests …

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

M Shariati, MS Mafipour, P Mehrabi, A Shariati… - Engineering with …, 2021 - Springer
Shear connectors play a prominent role in the design of steel-concrete composite systems.
The behavior of shear connectors is generally determined through conducting push-out …

A novel Harris hawks' optimization and k-fold cross-validation predicting slope stability

H Moayedi, A Osouli, H Nguyen… - Engineering with …, 2021 - Springer
Stability of the soil slopes is one of the most challenging issues in civil engineering projects.
Due to the complexity and non-linearity of this threat, utilizing simple predictive models does …

[HTML][HTML] Mathematical modeling techniques to predict the compressive strength of high-strength concrete incorporated metakaolin with multiple mix proportions

HU Ahmed, AA Abdalla, AS Mohammed… - Cleaner Materials, 2022 - Elsevier
Many environmental and health problems are raised from cement manufacturing processes
and other factories because those factories emit large amounts of carbon dioxide (CO 2) into …

Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic …

N Sathiparan, P Jeyananthan, DN Subramaniam - Measurement, 2024 - Elsevier
It is crucial to assess the characteristics of pervious concrete even post-construction. The
quality monitoring of such a procedure is tricky in pervious concrete that it is typically …

Systematic multiscale models to predict the compressive strength of self-compacting concretes modified with nanosilica at different curing ages

RH Faraj, AA Mohammed, A Mohammed… - Engineering with …, 2022 - Springer
The evolution of nanotechnology brings materials with novel performance and during last
year's much attempt has been established to include nanoparticles especially nano-silica …

Soft computing techniques to predict the compressive strength of green self-compacting concrete incorporating recycled plastic aggregates and industrial waste ashes

RH Faraj, AA Mohammed, KM Omer… - Clean Technologies and …, 2022 - Springer
Rapid urbanization and industrialization with corresponding economic growth have
increased concrete production, leading to resource depletion and environmental pollution …

A machine learning-based formulation for predicting shear capacity of squat flanged RC walls

DD Nguyen, VL Tran, DH Ha, VQ Nguyen, TH Lee - Structures, 2021 - Elsevier
The squat flanged reinforced concrete (RC) walls have been widely utilized in nuclear
power plant and building structures. Nevertheless, the empirical equations in current design …