Prediction and analysis of train arrival delay based on XGBoost and Bayesian optimization
R Shi, X Xu, J Li, Y Li - Applied Soft Computing, 2021 - Elsevier
Accurate train arrival delay prediction is critical for real-time train dispatching and for the
improvement of the transportation service. This study proposes a data-driven method that …
improvement of the transportation service. This study proposes a data-driven method that …
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost
Introduction In late 2019 and after the COVID-19 pandemic in the world, many researchers
and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study …
and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study …
Exploring interactive and nonlinear effects of key factors on intercity travel mode choice using XGBoost
Unraveling the complex relationships between intercity travel mode choices and their
determinants is valuable for transport planning and development. However, a better …
determinants is valuable for transport planning and development. However, a better …
A steel property optimization model based on the XGBoost algorithm and improved PSO
K Song, F Yan, T Ding, L Gao, S Lu - Computational Materials Science, 2020 - Elsevier
Exploring the relationships between the properties of steels and their compositions and
manufacturing parameters is extremely crucial and indispensable to understanding the …
manufacturing parameters is extremely crucial and indispensable to understanding the …
Review–Modern Data Analysis in Gas Sensors
MSI Sagar, NR Allison, HM Jalajamony… - Journal of The …, 2022 - iopscience.iop.org
Abstract Development in the field of gas sensors has witnessed exponential growth with
multitude of applications. The diverse applications have led to unexpected challenges …
multitude of applications. The diverse applications have led to unexpected challenges …
[HTML][HTML] Modeling of particle sizes for industrial HPGR products by a unique explainable AI tool-A “Conscious Lab” development
Abstract High-Pressure Grinding Rolls (HPGR), as a modified type of roll crushers, could
intensively reduce the energy consumptions in the mineral processing comminution units …
intensively reduce the energy consumptions in the mineral processing comminution units …
PM2. 5 and O3 concentration estimation based on interpretable machine learning
S Wang, Y Ren, B Xia - Atmospheric Pollution Research, 2023 - Elsevier
High concentrations of PM 2.5 and ozone (O 3) seriously threaten human health. In this
study, we constructed a machine learning-based model to predict PM 2.5 and O 3 …
study, we constructed a machine learning-based model to predict PM 2.5 and O 3 …
Structural performance prediction based on the digital twin model: A battery bracket example
W He, J Mao, K Song, Z Li, Y Su, Y Wang… - Reliability Engineering & …, 2023 - Elsevier
Battery bracket for new energy commercial vehicles is subjected to variable loads and
battery temperature changes both during the design road test phase and in-service …
battery temperature changes both during the design road test phase and in-service …
Extracting information on rocky desertification from satellite images: A comparative study
Rocky desertification occurs in many karst terrains of the world and poses major challenges
for regional sustainable development. Remotely sensed data can provide important …
for regional sustainable development. Remotely sensed data can provide important …
Dielectric constant prediction of pure organic liquids and their mixtures with water based on interpretable machine learning
J Deng, G Jia - Fluid Phase Equilibria, 2022 - Elsevier
The thermodynamic properties of mixed-solvent electrolytes are functions of pressure,
temperature, and composition (PTC), and are generally considered to be characterized by …
temperature, and composition (PTC), and are generally considered to be characterized by …