The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. by Ahmed M. Elshewey (21463867)

DE algorithm flow. by Ling Zhao (111365)

“…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …”

Classification results for all subsampling scenarios and algorithms for Gefitinib. by Sofia P. Miranda (11418930)

Test results of different algorithms. by Ling Zhao (111365)

“…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …”

Regression results for all combinations of subsampling scenarios and algorithms for Gefitinib. by Sofia P. Miranda (11418930)

Average RMSE rank for all combinations of subsampling scenarios and algorithms. by Sofia P. Miranda (11418930)

Summary of AUC values across all combinations of subsampling scenario and algorithm. by Sofia P. Miranda (11418930)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses by Meichen Liu (8168148)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

Subjects:

Minimum, mean and maximum RMSE value for each drug and algorithm combination, averaged across all subsampling scenarios. by Sofia P. Miranda (11418930)

Minimum, mean and maximum AUC value for each combination of drug and algorithm, averaged across all subsampling scenarios. by Sofia P. Miranda (11418930)

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. by Benjamin Gallois (10131683)

Correlation between predicted drug responses based on GDSC cell lines and recorded clinical responses in TCGA patients for selected combinations of subsampling scenarios and algori... by Sofia P. Miranda (11418930)

Relative predictive performance when using default algorithm hyperparameters and all features vs. tuning hyperparameters or selecting features. by Stephen R. Piccolo (8367780)

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement - Fig 4 by Antoine Falisse (6061601)

the functioning of BRPSO. by Hossein Jarrahi (22530251)

Descriptions of the algorithms we tested and hyperparameters that we evaluated via nested cross validation. by Sofia P. Miranda (11418930)

QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm by Z.Y. Algamal (5547620)

“…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

Game-relationship-based Remanufacturing Scheduling Model with Sequence-dependent Setup Times Using Improved Discrete Particle Swarm Algorithm by Anonymous Authors (for blind review purpose) (11523120)