Abstract
The Gaussian Process Regression (GPR), Decision Tree (DT), Relevance Vector Machine (RVM), and Artificial Neural Network (ANN) AI approaches are constructed in MATLAB R2020a with different hyperparameters namely, kernel function, leaf size, backpropagation algorithms, number of neurons and hidden layers to compute the permeability of soil. The present study is carried out using 158 datasets of soil. The soil dataset consists of fine content (FC), sand content (SC), liquid limit (LL), specific gravity (SG), plasticity index (PI), maximum dry density (MDD) and optimum moisture content (OMC), permeability (K). Excluding the permeability of soil, rest of properties of soil is used as input parameters of the AI models. The best architectural and optimum performance models are identified by comparing the performance of the models. Based on the performance of the AI models, the NISEK_K_GPR, 10LF_K_DT, Poly_K_RVM, and GDANN_K_10H5 models have been identified as the best architectural AI models. The comparison of performance of the best architectural models, it is observed that the NISEK_K_GPR model outperformed the other best architectural AI models. In this study, it is also observed that GPR model is outperformed ANN models because of small dataset. The performance of NISEK_K_GPR model is compared with models available in literature and it is concluded that the GPR model has better performance and least prediction error than models available in literature study.
Highlights
The soil consists of different shapes and size of particles, and these particles creates persistent or connected gaps
The literature survey shows that artificial intelligence approaches have the potential to predict the permeability of the soil
The Gaussian process regression, decision tree, relevance vector machine, and artificial neural network models have been developed with different hyperparameters in MATLAB R2020a to predict soil permeability
Summary
The soil consists of different shapes and size of particles, and these particles creates persistent or connected gaps. The characteristics of soil that allow the flow of water are called the permeability of soil [5]. The soil is classified as pervious, impervious, and semi-pervious if the permeability is more significant than 10-3 mm/sec, less than 10-5 mm/sec, and between 10-5 to 10-3 mm/sec, respectively as per USBR. The constant-head permeability test and variable head permeability test methods are laboratory methods and used to determine the permeability of soil. Revised Manuscript received on October 28, 2021.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Engineering and Advanced Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
