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 UCS of fine-grained soil based on machine learning part 1: multivariable regression analysis, gaussian process regression, and gene expression …
The present research introduces the best architecture approach and model for predicting the
unconfined compressive strength (UCS) of cohesive virgin soil by comparing the …
unconfined compressive strength (UCS) of cohesive virgin soil by comparing the …
Assessment of uniaxial strength of rocks: A critical comparison between evolutionary and swarm optimized relevance vector machine models
The present study compares the evolutionary and swarm-optimized relevance vector
machine (RVM) models to find the optimal model for computing rocks' uniaxial compressive …
machine (RVM) models to find the optimal model for computing rocks' uniaxial compressive …
Prediction of compaction and strength properties of amended soil using machine learning
WZ Taffese, KA Abegaz - Buildings, 2022 - mdpi.com
In the current work, a systematic approach is exercised to monitor amended soil reliability for
a housing development program to holistically understand the targeted material mixture and …
a housing development program to holistically understand the targeted material mixture and …
Indirect estimation of swelling pressure of expansive soil: GEP versus MEP modelling
In this article, detailed trials were undertaken to study the variation in genetic parameters in
order to formulate more robust predictive models using gene expression programming …
order to formulate more robust predictive models using gene expression programming …
Mechanical properties optimization and Simulation of soil–saw dust ash blend using extreme vertex design (EVD) method
This experimental investigation involves adaptation of constrained simplex mixture design
optimization technique for modeling of the mechanical behavior of soil–saw dust ash (SDA) …
optimization technique for modeling of the mechanical behavior of soil–saw dust ash (SDA) …
Quadratic discriminant analysis based ensemble machine learning models for groundwater potential modeling and map**
In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the
Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning …
Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning …
Soil quality assessment based on machine learning approach for cultivated lands in semi-humid environmental condition part of Black Sea region
To manage arable areas according to land resources for future generations, it is crucial to
determine the quality of the soils. The main purpose of this study is to identify soil quality for …
determine the quality of the soils. The main purpose of this study is to identify soil quality for …
Application of artificial intelligence to determined unconfined compressive strength of cement-stabilized soil in vietnam
HTT Ngo, TA Pham, HLT Vu, LV Giap - Applied Sciences, 2021 - mdpi.com
Cement stabilized soil is one of the commonly used as ground reinforcement solutions in
geotechnical engineering. In this study, the main object was to apply three machine learning …
geotechnical engineering. In this study, the main object was to apply three machine learning …