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 …
CBR prediction of pavement materials in unsoaked condition using LSSVM, LSTM-RNN, and ANN approaches
The present research introduces the best architecture model for predicting the unsoaked
California bearing ratio (CBRu) of soil by comparing the models based on the least square …
California bearing ratio (CBRu) of soil by comparing the models based on the least square …
CBR of stabilized and reinforced residual soils using experimental, numerical, and machine-learning approaches
This research employed coir fiber and activated carbon as eco-friendly additives and waste
materials while using lime as a traditional binder to improve the properties of two residual …
materials while using lime as a traditional binder to improve the properties of two residual …
Multi-output machine learning for addressing the trade-off between water permeability and wetting resistance in membrane distillation
J Ma, H Xu, M Zhang, A Wang, M Ding - Desalination, 2024 - Elsevier
Membrane distillation (MD) has gained extensive attention for the desalination of
hypersaline brine. Nevertheless, the performance of MD is often hampered by the inherent …
hypersaline brine. Nevertheless, the performance of MD is often hampered by the inherent …
Interpretable machine learning model for evaluating mechanical properties of concrete made with recycled concrete aggregate
The main objective of this paper is to use the data‐driven approach to predict and evaluate
the mechanical properties of concrete made with recycled concrete aggregate (RCA) …
the mechanical properties of concrete made with recycled concrete aggregate (RCA) …
Intelligent mixture optimization for stabilized soil containing solid waste based on machine learning and evolutionary algorithms
J Wang, G Chen, Y Chen, Z Ye, M Lin, R Su… - Construction and Building …, 2024 - Elsevier
The usage of industrial solid waste to improve soil for road materials has attracted
widespread attention. In addition to mechanical performance, economic and environmental …
widespread attention. In addition to mechanical performance, economic and environmental …
[HTML][HTML] Dynamics and causes of cropland Non-Agriculturalization in typical regions of China: An explanation Based on interpretable Machine learning
G Zhang, X Li, L Zhang, X Wei - Ecological Indicators, 2024 - Elsevier
Cropland resources are crucial for food security and economic development. As a populous
nation that considers cropland a valuable strategic resource, China has faced challenges of …
nation that considers cropland a valuable strategic resource, China has faced challenges of …
Data-driven approach in investigating and predicting unconfined compressive strength of cemented paste backfill
QT Ngo, CT Ngo, QH Nguyen, HN Nguyen… - Materials Today …, 2023 - Elsevier
Eight machine learning (ML) models including 6 shallow ML including XGB, GB, RF, LGB,
SVR, KNN and 2 hybrid ML models consisting of XGB_P (Particle Swarm Optimization) and …
SVR, KNN and 2 hybrid ML models consisting of XGB_P (Particle Swarm Optimization) and …
Exploring sustainable solutions for soil stabilization through explainable Gaussian process-assisted multi-objective optimization
The adoption of sustainable solutions in soil stabilization has piqued the interest of the
scientific community due to the potential reduction in carbon footprint. In this regard, the …
scientific community due to the potential reduction in carbon footprint. In this regard, the …
Application of KRR, K-NN and GPR algorithms for predicting the soaked CBR of fine-grained plastic soils
California bearing ratio (CBR) test is one of the comprehensive tests used for the last few
decades to design the pavement thickness of roadways, railways and airport runways …
decades to design the pavement thickness of roadways, railways and airport runways …