[HTML][HTML] Machine learning and remote sensing techniques applied to estimate soil indicators–review
The demand for food based on intensive agriculture has decreased soil quality, posing great
challenges such as increasing agricultural productivity and promoting environmental …
challenges such as increasing agricultural productivity and promoting environmental …
Challenges and opportunities in remote sensing for soil salinization mapping and monitoring: A review
Meeting current needs without compromising future generations' ability to meet theirs is the
only path toward achieving environmental sustainability. As the most valuable natural …
only path toward achieving environmental sustainability. As the most valuable natural …
[HTML][HTML] Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization
Accurate assessment of undrained shear strength (USS) for soft sensitive clays is a great
concern in geotechnical engineering practice. This study applies novel data-driven extreme …
concern in geotechnical engineering practice. This study applies novel data-driven extreme …
Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate
The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …
parameter for the successful accomplishment of a tunneling project, and the proper and …
Optimization of random forest through the use of MVO, GWO and MFO in evaluating the stability of underground entry-type excavations
The stability evaluation of underground entry-type excavations is a prerequisite of the entry-
type mining method, which directly affects whether workers can be provided with a safe and …
type mining method, which directly affects whether workers can be provided with a safe and …
Employing a genetic algorithm and grey wolf optimizer for optimizing RF models to evaluate soil liquefaction potential
Among the research hotspots in geological/geotechnical engineering, research on the
prediction of soil liquefaction potential is still limited. In this research, several machine …
prediction of soil liquefaction potential is still limited. In this research, several machine …
[HTML][HTML] Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization
The advance rate (AR) of a tunnel boring machine (TBM) under hard rock conditions is a key
parameter in the successful implementation of tunneling engineering. In this study, we …
parameter in the successful implementation of tunneling engineering. In this study, we …
Prediction of ground vibration induced by blasting operations through the use of the Bayesian Network and random forest models
The present study aims to compare the performance of two machine learning techniques
that can unveil the relationship between the input and target variables and predict the …
that can unveil the relationship between the input and target variables and predict the …
[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 …
Slope stability prediction for circular mode failure using gradient boosting machine approach based on an updated database of case histories
Prediction of slope stability is one of the most crucial tasks in mining and geotechnical
engineering projects. The accuracy of the prediction is very important for mitigating the risk …
engineering projects. The accuracy of the prediction is very important for mitigating the risk …