Modelling and validation of liquefaction potential index of fine-grained soils using ensemble learning paradigms

S Ghani, SC Sapkota, RK Singh, A Bardhan… - Soil Dynamics and …, 2024 - Elsevier
This study explores the utilization of ensemble-based soft computing techniques for
predicting the liquefaction potential of fine-grained soils. Generally, deterministic methods …

Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients

N Kardani, A Bardhan, P Samui, M Nazem… - International Journal of …, 2022 - Elsevier
This study aims to propose hybrid adaptive neuro swarm intelligence (HANSI) techniques for
predicting the thermal conductivity of unsaturated soils. The novel contribution is made by …

Soft computing techniques for the prediction of concrete compressive strength using Non-Destructive tests

PG Asteris, AD Skentou, A Bardhan, P Samui… - … and Building Materials, 2021 - Elsevier
This study presents a comparative assessment of conventional soft computing techniques in
estimating the compressive strength (CS) of concrete utilizing two non-destructive tests …

ELM-based adaptive neuro swarm intelligence techniques for predicting the California bearing ratio of soils in soaked conditions

A Bardhan, P Samui, K Ghosh, AH Gandomi… - Applied Soft …, 2021 - Elsevier
This study proposes novel integration of extreme learning machine (ELM) and adaptive
neuro swarm intelligence (ANSI) techniques for the determination of California bearing ratio …

Prediction of UCS of fine-grained soil based on machine learning part 1: multivariable regression analysis, gaussian process regression, and gene expression …

J Khatti, KS Grover - Multiscale and multidisciplinary modeling …, 2023 - Springer
The present research introduces the best architecture approach and model for predicting the
unconfined compressive strength (UCS) of cohesive virgin soil by comparing the …

Prediction of the seismic effect on liquefaction behavior of fine-grained soils using artificial intelligence-based hybridized modeling

S Ghani, S Kumari, S Ahmad - Arabian Journal for Science and …, 2022 - Springer
Researchers in the past have reported significant uncertainties involved in evaluating the
risk of soil liquefaction using deterministic approaches. Therefore, to improve the accuracy …

Machine learning approaches for real-time prediction of compressive strength in self-compacting concrete

S Ghani, N Kumar, M Gupta, S Saharan - Asian Journal of Civil …, 2024 - Springer
Self-compacting concrete (SCC) has transformed civil engineering by efficiently filling
formwork without mechanical consolidation, enhancing construction efficiency, and …

A novel improved Harris Hawks optimization algorithm coupled with ELM for predicting permeability of tight carbonates

N Kardani, A Bardhan, B Roy, P Samui… - Engineering with …, 2022 - Springer
Tight carbonate reservoirs appear to be heterogeneous due to the patchy production of
various digenetic properties. Consequently, the permeability calculation of tight rocks is …

Liquefaction behavior of Indo-Gangetic region using novel metaheuristic optimization algorithms coupled with artificial neural network

S Ghani, S Kumari - Natural Hazards, 2022 - Springer
The present research aims to co-relate the plasticity and liquefaction response of soil as well
as its significance in defining liquefaction probability. To accomplish this, metaheuristic …