Prediction of ecofriendly concrete compressive strength using gradient boosting regression tree combined with GridSearchCV hyperparameter-optimization …

ZM Alhakeem, YM Jebur, SN Henedy, H Imran… - Materials, 2022 - mdpi.com
A crucial factor in the efficient design of concrete sustainable buildings is the compressive
strength (Cs) of eco-friendly concrete. In this work, a hybrid model of Gradient Boosting …

Machine learning models for occurrence form prediction of heavy metals in tailings

J Zheng, M Wu, ZM Yaseen, C Qi - International Journal of Mining …, 2023 - Taylor & Francis
Modern mining and metal ore smelting produce vast tailings, increasing heavy metal
pollution. The study of heavy metal occurrence forms is a promising way to remediate …

Ensemble machine-learning-based prediction models for the compressive strength of recycled powder mortar

Z Fei, S Liang, Y Cai, Y Shen - Materials, 2023 - mdpi.com
Recycled powder (RP) serves as a potential and prospective substitute for cementitious
materials in concrete. The compressive strength of RP mortar is a pivotal factor affecting the …

[HTML][HTML] Application of supervised learning algorithms for temperature prediction in nucleate flow boiling

A Cabarcos, C Paz, E Suarez, J Vence - Applied Thermal Engineering, 2024 - Elsevier
This work investigates the use of supervised learning algorithms to predict temperatures in
an experimental test bench, which was initially designed for studying nucleate boiling …

[HTML][HTML] Effects of wet grinding combined with chemical activation on the activity of iron tailings powder

Y Yang, Z Yang, Z Cheng, H Zhang - Case Studies in Construction …, 2022 - Elsevier
Utilizing iron tailings powder (ITP) as supplementary cementitious materials (SCMs) has
significant economic and environmental benefits, while the low pozzolanic activity of ITP …

Ensemble machine learning and Shapley additive explanations for the ability of CSH seeds to accelerate cement hydration

Y Yang, Z Cheng - Journal of Materials Science, 2024 - Springer
Due to the complexity of the reaction mechanism of calcium-silicate-hydrate (CSH) seeds in
cement, the influence pattern of various factors, especially Ca/Si, on the acceleration ability …

[HTML][HTML] Machine Learning for Predicting Compressive Strength of Sustainable Cement Paste Incorporating Copper Mine Tailings as Supplementary Cementitious …

EO Kurniati, H Zeng, MI Latypov, HJ Kim - Case Studies in Construction …, 2024 - Elsevier
Copper mining produces significant amounts of copper mine tailings (CMT), necessitating
appropriate waste handling and disposal practices. By substituting a portion of cement with …

A Novel Approach for Model Interpretability and Domain Aware Fine-Tuning in AdaBoost

RJ Kiran, J Sanil, S Asharaf - Human-Centric Intelligent Systems, 2024 - Springer
The success of machine learning in real-world use cases has increased its demand in
mission-critical applications such as autonomous vehicles, healthcare and medical …

Sustainable approach towards alternatives for the use of iron ore tailings in the construction sector using Data Envelopment Analysis methodology

WC de Oliveira, SR de Araújo… - Waste Management …, 2024 - journals.sagepub.com
Iron ore tailings (IOTs) need to be properly managed to mitigate the environmental, social,
and economic impacts of mining activities. To cope with this issue, we use data envelopment …

[HTML][HTML] Prediction of compressive strength of recycled concrete using gradient boosting models

AHA Ahmed, W Jin, MAH Ali - Ain Shams Engineering Journal, 2024 - Elsevier
The construction industry is shifting towards sustainability, emphasizing the need for
innovative materials. Recycled Aggregate Concrete (RAC), utilizing recycled aggregates …