A scientometrics review of soil properties prediction using soft computing approaches
In this world, several types of soils are available with their different engineering properties.
Determining each soil's engineering properties is difficult because the laboratory procedures …
Determining each soil's engineering properties is difficult because the laboratory procedures …
[HTML][HTML] Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models
A comparison between deep learning and standalone models in predicting the compaction
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
Prediction of compaction parameters of compacted soil using LSSVM, LSTM, LSBoostRF, and ANN
The present research introduces a robust approach for predicting the maximum dry density
(MDD) and optimum moisture content (OMC) of compacted soil by comparing models based …
(MDD) and optimum moisture content (OMC) of compacted soil by comparing models based …
Prediction of soaked CBR of fine-grained soils using soft computing techniques
The present research determines the effect of training data sets, correlation, and
multicollinearity on the performance and overfitting of gene expression programming (GEP) …
multicollinearity on the performance and overfitting of gene expression programming (GEP) …
Utilization of support vector models and gene expression programming for soil strength modeling
AR Tenpe, A Patel - Arabian Journal for Science and Engineering, 2020 - Springer
The subgrade strength of roads and highways is based on the California bearing ratio (CBR)
value. In this investigation, attempts have been made to overcome the limited boundary …
value. In this investigation, attempts have been made to overcome the limited boundary …
Surrogate models to predict maximum dry unit weight, optimum moisture content and California bearing ratio form grain size distribution curve
S Alzabeebee, SA Mohamad… - Road Materials and …, 2022 - Taylor & Francis
This study evaluates the applicability of using a robust, novel, data-driven method in
proposing surrogate models to predict the maximum dry unit weight, optimum moisture …
proposing surrogate models to predict the maximum dry unit weight, optimum moisture …
Prediction of the California bearing ratio (CBR) of compacted soils by using GMDH-type neural network
The California bearing ratio (CBR) is an important parameter in defining the bearing
capacity of various soil structures, such as earth dams, road fillings and airport pavements …
capacity of various soil structures, such as earth dams, road fillings and airport pavements …
Use of neural networks for the prediction of the CBR value of some Aegean sands
Y Erzin, D Turkoz - Neural Computing and Applications, 2016 - Springer
This study deals with the development of an artificial neural network (ANN) and a multiple
regression (MR) model that can be employed for estimating the California bearing ratio …
regression (MR) model that can be employed for estimating the California bearing ratio …
Evaluation of SPT-N values and internal friction angle correlation using artificial intelligence methods in granular soils
AB Ekmen - Soil Research, 2023 - eshop.publish.csiro.au
Context Artificial neural networks (ANNs) and genetic algorithms (GAs) have become widely
used in various engineering fields due to their ability to solve complicated issues directly …
used in various engineering fields due to their ability to solve complicated issues directly …
[PDF][PDF] Correlation of CBR with index properties of soil
ZS Janjua, J Chand - International Journal of Civil Engineering and …, 2016 - academia.edu
California bearing ratio (CBR) test is performed to determine the stiffness modulus and
shear strength of sub grade which is used for the design of flexible pavement of runways of …
shear strength of sub grade which is used for the design of flexible pavement of runways of …