Accurately predicting the Modulus of Resilience (MR) of subgrade soils, which exhibit non-
linear stress–strain behaviors, is crucial for effective soil assessment. Traditional laboratory …

This investigation introduces the optimal performance models for predicting the compressive
strength (CS) and pozzolanic activity index (PAI) by comparing the machine learning …

Drought stands as a highly perilous natural catastrophe that impacts numerous facets of
human existence. Drought data is nonstationary and noisy, posing challenges for accurate …

Due to the limited features and poor accuracy of current methods for predicting the dynamic
response of subgrades, this paper proposes an innovative approach that combines …

The design of cementitious mixtures incorporating mine tailings as fine aggregates is a multi-
objective optimization (MOO) problem, in which both the uniaxial compressive strength …

This study presents a comprehensive evaluation of the resilient modulus of unsaturated
subgrade soils using a novel in-situ modulus detector (IMD) along with various laboratory …

The present investigation employs relevance vector machine (RVM) and long short-term
memory (LSTM) models to predict the time-dependent bearing capacity of concrete piles …

Electrokinetic remediation (EKR) presents a promising approach for polluted soil
remediation, leveraging electric fields to mobilize contaminants and facilitate their removal …

Accurate estimation of the soil resilient modulus (MR) is essential for designing and
monitoring pavements. However, experimental methods tend to be time-consuming and …

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by inflammation
and pain in the joints, which can lead to joint damage and disability over time …