Machine learning and interactive GUI for concrete compressive strength prediction

MK Elshaarawy, MM Alsaadawi, AK Hamed - Scientific Reports, 2024 - nature.com
Concrete compressive strength (CS) is a crucial performance parameter in concrete
structure design. Reliable strength prediction reduces costs and time in design and prevents …

[HTML][HTML] Hybrid machine learning approach to prediction of the compressive and flexural strengths of UHPC and parametric analysis with shapley additive …

P Das, A Kashem - Case Studies in Construction Materials, 2024 - Elsevier
Ultra-high-performance concrete (UHPC) is a sustainable construction material; it can be
applied as a substitute for cement concrete. Artificial intelligence methods have been used …

[HTML][HTML] Compressive strength prediction of sustainable concrete incorporating rice husk ash (RHA) using hybrid machine learning algorithms and parametric …

A Kashem, R Karim, P Das, SD Datta… - Case Studies in …, 2024 - Elsevier
The construction industry is making efforts to reduce the environmental impact of cement
production in concrete by incorporating alternative and supplementary cementitious …

[HTML][HTML] Sustainability-oriented construction materials for traditional residential buildings: From material characteristics to environmental suitability

C Wang, Y Zhang, X Hu, X Jia, K Li, C Wang… - Case Studies in …, 2024 - Elsevier
The increasing replacement of traditional construction materials with modern alternatives
often overlooks their superior environmental adaptability and sustainability, resulting in …

Shear behavior of reinforced concrete beams comprising a combination of crumb rubber and rice husk ash

MAM Hassanean, SAM Hussein, M Elsayed - Engineering Structures, 2024 - Elsevier
In this paper, experimental studies were conducted to examine the shear behavior of
reinforced concrete beams, including a combination of crumb rubber (CR) and rice husk ash …

Tree-based machine learning models for predicting the bond strength in reinforced recycled aggregate concrete

A Mahmoudian, M Bypour, DPN Kontoni - Asian Journal of Civil …, 2024 - Springer
To address the ever-increasing environmental degradation caused by concrete construction,
utilizing recycled aggregate (RA) in concrete mixes offers a significant solution. This study …

A comparative study of machine learning models for construction costs prediction with natural gradient boosting algorithm and SHAP analysis

P Das, A Kashem, I Hasan, M Islam - Asian Journal of Civil Engineering, 2024 - Springer
The precise prediction of construction costs during the initial phase of a construction project
is crucial for ensuring the project's success. Identifying the parameters that influence project …

Optimizing compressive strength prediction using adversarial learning and hybrid regularization

T Aziz, H Aziz, S Mahapakulchai… - Scientific Reports, 2024 - nature.com
The infrastructure industry consumes natural resources and produces construction waste,
which has a detrimental impact on the environment. To mitigate these adverse effects and …

Development and validation of machine learning models for diagnosis and prognosis of lung adenocarcinoma, and immune infiltration analysis

L Lin, Y Bao - Scientific Reports, 2024 - nature.com
The aim of our study was to develop robust diagnostic and prognostic models for lung
adenocarcinoma (LUAD) using machine learning (ML) techniques, focusing on early …

Improved forecasting of the compressive strength of ultra‐high‐performance concrete (UHPC) via the CatBoost model optimized with different algorithms

M Katlav, F Ergen - Structural Concrete, 2024 - Wiley Online Library
This paper focuses on the applicability of CatBoost models constructed using various
optimization techniques for improved forecasting the compressive strength of ultra‐high …