Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

System no-load torque response results under three control algorithms. by Haoran Cui (7235234)

Subjects: “…Cell Biology…”

Mean and standard deviation of RBF classifier performance across different training algorithms with cross-validation. by Mohammad Hossein Hadizadeh Isfahani (22634016)

Mean and standard deviation of MLP classifier performance across different training algorithms with cross-validation. by Mohammad Hossein Hadizadeh Isfahani (22634016)

The empirical distribution function and fitted distribution functions for data sets <i>Q</i> and <i>T</i>. by Salem A. Alyami (10572611)

(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

Subjects:

Interactive visualization of ocean unsteady flow data based on dynamic adaptive pathline by Fenglin Tian (6002957)

“…This study presents an interactive visualization algorithm designed for the spatio-temporal correlated ocean unsteady flow field utilizing dynamic adaptive pathlines. …”

Wilcoxon p-value of the en-CSA vs baseline algorithms for CEC2020. by Sarah A. Alzakari (19704611)

Subjects:

Functional analysis of anoikis-related genes. by Yufeng He (5673119)

Subjects:

Top-ranked hub genes identified by 5 cytoHubba algorithms. by Jun Li (6494)

Schematic diagram of sliding mode variable structure control algorithm design content. by Haoran Cui (7235234)

Subjects: “…Cell Biology…”

Framework of MAPPO. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

The average completion time of each method. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

The connection of physical space. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

End-to-end data transmission delay. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Production workflow of stiffened H-beams. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Collision risk warning. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Framework of rMAPPO. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Data_and_model_files. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Machine learning analysis of 10 hub genes related to SCI was performed using eight algorithms applied to the dataset. by Tianbao Feng (21722233)