Geospatial intelligence in geotechnical engineering: a comprehensive investigation into SPT-N, soil types, and undrained shear strength for enhanced site …

W Hassan, M Qasim, B Alshameri, A Shahzad… - Bulletin of Engineering …, 2024 - Springer
The primary challenges in metropolitan planning, selection of sites, and developing
preemptive safety measures lie in the characterization and precise appraisal of underground …

A sustainable approach for estimating soft ground soil stiffness modulus using artificial intelligence

MN Nawaz, MM Nawaz, TA Awan, STA Jaffar… - Environmental Earth …, 2023 - Springer
Soft soils pose significant challenges to the environment and construction of infrastructure
on them owing to their distinct characteristics such as low bearing strength, high water …

[HTML][HTML] Optimal Cost Design of RC T-Shaped Combined Footings

VM Moreno-Landeros, A Luévanos-Rojas… - Buildings, 2024 - mdpi.com
This paper shows the optimal cost design for T-shaped combined footings of reinforced
concrete (RC), which are subjected to biaxial bending in each column to determine the steel …

Mathematical Modeling of the Optimal Cost for the Design of Strap Combined Footings

A Luévanos-Rojas, G Santiago-Hurtado… - Mathematics, 2024 - mdpi.com
This paper presents a novel mathematical model to determine the minimum cost for the
design of reinforced-concrete strap combined footings under biaxial bending, with each …

Estimation of impedance features and classification of carcinoma breast cancer using optimization techniques

M Asadi - BioMedInformatics, 2023 - mdpi.com
Breast cancer is the most prevalent form of cancer and the primary cause of cancer-related
mortality among women globally. Breast cancer diagnosis involves multiple variables …

Utilizing undisturbed soil sampling approach to predict elastic modulus of cohesive soils: a Gaussian process regression model

MN Nawaz, MHA Khan, W Hassan, STA Jaffar… - … Experiments and Design, 2024 - Springer
This study addresses a critical issue of sample disturbance in predicting the elastic modulus
(E s) of soft cohesive soils using machine learning techniques. Traditional approaches either …

Prediction of California bearing ratio using hybrid regression models

W Wang, L Zhao, D Dong - Signal, Image and Video Processing, 2024 - Springer
CBR assesses the subgrade strength of road infrastructure, typically requiring time-
consuming laboratory testing. In this study, Machine Learning (ML) has been used to avoid …

Roll dynamic coefficients approach of decay test using the generalized reduced gradient method (grg)

H Hasanudin, A Zubaydi… - Journal of Applied …, 2023 - aseestant.ceon.rs
Sea transportation is the vehicle which dominant and vital in the world. The increasing
number of ships, types, and uncertain climate change have caused many ship accidents that …

OPTIMAL SIZING OF HYBRID MICROGRIDS WITH CONSIDERATION OF GLOBAL WARMING EFFECTS: A MARS AND GRG APPROACH

Y YILMAZ - 2024 - open.metu.edu.tr
This study from the METU North Cyprus Campus projects load and power demands
spanning from 2026 to 2050, integrating regional global warming forecasts from the IPCC's …

ESTIMATING GROUNDWATER ELEVATION USING MACHINE LEARNING TECHNIQUES: A CASE OF METRO MANILA, PHILIPPINES

J Galupino, J Dungca - i-asem.org
Groundwater elevation is a significant factor in Geotechnical Engineering because it has a
significant effect on the strength, stability, and deformation characteristics of soils, as well as …