Efficient computational techniques for predicting the California bearing ratio of soil in soaked conditions

A Bardhan, C Gokceoglu, A Burman, P Samui… - Engineering …, 2021 - Elsevier
California bearing ratio (CBR) is one of the important parameters that is used to express the
strength of the pavement subgrade of railways, roadways, and airport runways. CBR is …

Multivariate Adaptive Regression Splines (MARS) approach to blast-induced ground vibration prediction

CK Arthur, VA Temeng, YY Ziggah - International journal of mining …, 2020 - Taylor & Francis
Modelling and prediction of blast-induced ground vibration is a significant aspect of mining
and civil engineering operations, as ground vibration has dire consequences on both the …

An improved whale optimization algorithm for locating critical slip surface of slopes

SH Li, XH Luo, LZ Wu - Advances in Engineering Software, 2021 - Elsevier
Locating a critical slip surface or calculating the minimum safety factor of a slope is important
in geotechnical engineering, and also involves a complex optimization problem. A novel …

Spatial modeling of susceptibility to subsidence using machine learning techniques

M Mohammady, HR Pourghasemi, M Amiri… - … Research and Risk …, 2021 - Springer
Land subsidence is a hazard that results from conditioning factors that cause environmental
change and generate social and economic impacts. Some of these factors may increase …

Soft computing-based prediction of CBR values

S Kamrul Alam, A Shiuly - Indian Geotechnical Journal, 2024 - Springer
Abstract California Bearing Ratio method is an empirical method of design of flexible
pavement developed by California Division of Highways, in 1928 for the design of …

Assessing, mapping, and optimizing the locations of sediment control check dams construction

HR Pourghasemi, S Yousefi, N Sadhasivam… - Science of the total …, 2020 - Elsevier
Check dams are considered to be one of the most effective measures for conservation of the
soil and water resources. However, identifying the most suitable sites for the installation of …

Slope stability evaluation using backpropagation neural networks and multivariate adaptive regression splines

Z Liao, Z Liao - Open Geosciences, 2020 - degruyter.com
Slope stability assessment is a critical concern in construction projects. This study explores
the use of multivariate adaptive regression splines (MARS) to capture the intrinsic nonlinear …

A geometry-based slip prediction model for planetary rovers

H Ma, H Yang, Q Li, S Liu - Computers & Electrical Engineering, 2020 - Elsevier
Wheeled robots commonly undergo slip in various types of natural terrains, particularly in
planetary exploration missions. Therefore, it is important to predict slip from a distance for …

Badland erosion susceptibility mapping using machine learning data mining techniques, Firozkuh watershed, Iran

M Mohammady - Natural Hazards, 2023 - Springer
Badlands are landforms related to runoff, with dissected V-shaped valleys, short steep
slopes, and high drainage density, and results from a very important type of erosion that …

Coupling elephant herding with ordinal optimization for solving the stochastic inequality constrained optimization problems

SC Horng, SS Lin - Applied Sciences, 2020 - mdpi.com
The stochastic inequality constrained optimization problems (SICOPs) consider the
problems of optimizing an objective function involving stochastic inequality constraints. The …