Bayesian neural network-based uncertainty modelling: application to soil compressibility and undrained shear strength prediction
P Zhang, ZY Yin, YF Jin - Canadian Geotechnical Journal, 2022 - cdnsciencepub.com
This study adopts the Bayesian neural network (BNN) integrated with a strong non-linear
fitting capability and uncertainty, which has not previously been used in geotechnical …
fitting capability and uncertainty, which has not previously been used in geotechnical …
Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based …
This research investigates and compares the performance of three tree-based Machine
Learning (ML) methods, Canonical Correlation Forest (CCF), Rotation Forest (RotFor), and …
Learning (ML) methods, Canonical Correlation Forest (CCF), Rotation Forest (RotFor), and …
Prediction of shield machine attitude based on various artificial intelligence technologies
H Xiao, B Xing, Y Wang, P Yu, L Liu, R Cao - Applied Sciences, 2021 - mdpi.com
The shield machine attitude (SMA) is the most important parameter in the process of tunnel
construction. To prevent the shield machine from deviating from the design axis (DTA) of the …
construction. To prevent the shield machine from deviating from the design axis (DTA) of the …
An advanced meta-learner based on artificial electric field algorithm optimized stacking ensemble techniques for enhancing prediction accuracy of soil shear strength
Shear strength is a crucial property of soils regarded as its intrinsic capacity to resist failure
when forces act on the soil mass. This study proposes an advanced meta-leaner to discern …
when forces act on the soil mass. This study proposes an advanced meta-leaner to discern …
Comparative study of hybrid artificial intelligence approaches for predicting peak shear strength along soil-geocomposite drainage layer interfaces
Z Chao, G Fowmes, SM Dassanayake - International Journal of …, 2021 - Springer
Peak shear strength of soil-Geocomposite Drain Layer (GDL) interfaces is an important
parameter in the designing and operating related engineering structures. In this paper, a …
parameter in the designing and operating related engineering structures. In this paper, a …
Examination of the correlation between SPT and undrained shear strength: Case study of clay till in Alberta, Canada
C Kang, M Brotherton, K Anderson, K Semeniuk… - Engineering …, 2024 - Elsevier
In this study, we introduce a novel method for estimating undrained shear strength (C u) by
incorporating SPT depth. A comprehensive dataset of 328 data groups from locations in …
incorporating SPT depth. A comprehensive dataset of 328 data groups from locations in …
Performance evaluation of hybrid YYPO-RF, BWOA-RF and SMA-RF models to predict plastic zones around underground powerhouse caverns
Accurately predicting the extent of the plastic zone around the underground powerhouse
cavern is an important basis for the excavation and support design of underground space …
cavern is an important basis for the excavation and support design of underground space …
Prediction of undrained shear strength by the GMDH-type neural network using SPT-value and soil physical properties
M Kim, O Okuyucu, E Ordu, S Ordu, Ö Arslan, J Ko - Materials, 2022 - mdpi.com
This study presents a novel method for predicting the undrained shear strength (cu) using
artificial intelligence technology. The cu value is critical in geotechnical applications and …
artificial intelligence technology. The cu value is critical in geotechnical applications and …
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear …
In the field of data engineering in machine learning (ML), a crucial component is the process
of scaling, normalization, and standardization. This process involves transforming data to …
of scaling, normalization, and standardization. This process involves transforming data to …
Influence of grain shape on stress-dilatancy parameters
C Arda, O Cinicioglu - Granular Matter, 2021 - Springer
This study experimentally investigates the influences of grain shape and gradation on stress-
dilatancy parameters. For this purpose, consolidated-drained triaxial tests are conducted on …
dilatancy parameters. For this purpose, consolidated-drained triaxial tests are conducted on …