Semiconductor laser system parameters and parameter optimization table. حسب Jian Kong (164512)

Table of relationships between algorithms and five strategies for two experimental groups. حسب Jin Zhang (53297)

ANOVA table for power and surface roughness. حسب Pramod S. Kathmore (20410298)

Details of 23 basic benchmark functions. حسب Ying Li (38224)

Q-Table values for each state-action pair at selected generations (mean over 20 runs). حسب Zhongfeng Li (3965060)

Table1_Short-term wind power prediction based on anomalous data cleaning and optimized LSTM network.DOCX حسب Wu Xu (205838)

Table2_Short-term wind power prediction based on anomalous data cleaning and optimized LSTM network.DOCX حسب Wu Xu (205838)

Route for bays29 output by ABSQL algorithm. حسب Jin Zhang (53297)

"…DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive <i>ε-beam</i> search strategy, and a new Q-value update formula. …"

-orthogonal experiment table and results. حسب Kuiyuan Pan (21145338)

Optimal route of bays29. حسب Jin Zhang (53297)

"…DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive <i>ε-beam</i> search strategy, and a new Q-value update formula. …"

Table1_Optimized coordinated control method with virtual inertia based on fractional impedance model for charging stations.XLSX حسب Jiang Li (272926)

Table2_Optimized coordinated control method with virtual inertia based on fractional impedance model for charging stations.XLSX حسب Jiang Li (272926)

Table3_Optimized coordinated control method with virtual inertia based on fractional impedance model for charging stations.XLSX حسب Jiang Li (272926)

Robustness of the optimization process in a real dataset. حسب Neta Ravid Tannenbaum (2940351)

P-value Analysis for statistical validation of the hybrid model against deep learning models. This analysis extends the validation in Table 9 to advanced deep learning architecture... حسب Medhat A. Tawfeek (22522087)

Clinical diagnostic efficacy comparison of the proposed hybrid model and benchmark machine learning models. Metrics are reported as point estimates with 95% CIs. This table offers... حسب Medhat A. Tawfeek (22522087)

Table3_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.xlsx حسب Roberto Martin-Hernandez (3661549)

Table1_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.xlsx حسب Roberto Martin-Hernandez (3661549)

Table2_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.XLSX حسب Roberto Martin-Hernandez (3661549)

Table 1_The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients.docx حسب Zhou Liu (1506679)