Soft computing models for prediction of bentonite plastic concrete strength

WB Inqiad, MF Javed, K Onyelowe, MS Siddique… - Scientific Reports, 2024 - nature.com
Bentonite plastic concrete (BPC) is extensively used in the construction of water-tight
structures like cut-off walls in dams, etc., because it offers high plasticity, improved …

Machine learning prediction of the unconfined compressive strength of controlled low strength material using fly ash and pond ash

KL Dev, DR Kumar, W Wipulanusat - Scientific Reports, 2024 - nature.com
The sustainable use of industrial byproducts in civil engineering is a global priority,
especially in reducing the environmental impact of waste materials. Among these, coal ash …

A novel tool for probabilistic modeling of liquefaction behavior in alluvial soil

S Ghani, S Kumari - Georisk: Assessment and Management of Risk …, 2024 - Taylor & Francis
This research introduces and validates advanced machine learning models designed to
predict the probability of liquefaction failure (pf) in alluvial soil deposits. Three optimisation …

Prediction of California Bearing Ratio of nano-silica and bio-char stabilized soft sub-grade soils using explainable machine learning

I Thapa, S Ghani, KA Waris, BM Basha - Transportation Geotechnics, 2024 - Elsevier
This study investigates the prediction of the California Bearing Ratio (CBR) for nano-silica
and bio-char stabilized soft sub-grade soils using explainable machine learning (ML) …

Applications of computational intelligence for predictive modeling of properties of blended cement sustainable concrete incorporating various industrial byproducts …

NP Mungle, DM Mate, SH Mankar, VT Tale… - Asian Journal of Civil …, 2024 - Springer
The quest to enhance the strength of concrete, while at the same time reducing the
environmental impacts occasioned by its use, has become quite imperative in sustainable …

Advancing earth science in geotechnical engineering: A data-driven soft computing technique for unconfined compressive strength prediction in soft soil

I Thapa, S Ghani - Journal of Earth System Science, 2024 - Springer
This study presents a pioneering approach that combines artificial intelligence and a nature-
inspired optimization algorithm to predict soil unconfined compressive strength (UCS). The …

A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure

SV Singh, S Ghani - Frontiers in Built Environment, 2024 - frontiersin.org
This paper presents a novel approach for assessing liquefaction potential by integrating
Dynamic Cone Penetration Test (DCPT) data with advanced machine learning (ML) …

Enhancing unconfined compressive strength prediction in nano-silica stabilized soil: a comparative analysis of ensemble and deep learning models

I Thapa, S Ghani - Modeling Earth Systems and Environment, 2024 - Springer
The study emphasizes the challenges of determining the Unconfined Compressive Strength
(UCS) of soil stabilized using nano-silica (NS) in civil engineering applications. As a result, a …

Internal Stability of Mechanically Stabilized Earth Wall Using Machine Learning Techniques

R Mustafa, MT Ahmad - Transportation Infrastructure Geotechnology, 2024 - Springer
This paper proposes an AI-based prediction method for factor of safety (FOS) against rupture
and pull-out failure and examines and compares the applicability and adaptability of k …

Compressive strength of bentonite concrete using state-of-the-art optimised XGBoost models

P Kumar, S Shekhar Kamal, A Kumar… - Nondestructive …, 2024 - Taylor & Francis
This study proposes an advanced soft-computing approach for predicting the compressive
strength (CS) of bentonite concrete using an optimised XGBoost model. Bentonite is valued …