Flowchart of the phase optimization algorithm. by Maxim Terekhov (3429614)

The initial and final values for each PSO parameter in all application. by Rutinaldo Aguiar Nascimento (14259594)

WSN optimized by different algorithms. by Qingwen Meng (156386)

“…<div><p>This study develops an enhanced Secretary Bird Optimization Algorithm (ASBOA) based on the original Secretary Bird Optimization Algorithm (SBOA), aiming to further improve the solution accuracy and convergence speed for wireless sensor network (WSN) deployment and engineering optimization problems. …”

Flow chart of particle swarm algorithm. by Nour Eldeen Mahmoud Khalifa (19259450)

“…The third phase is the training and testing phase. Finally, the best-performing model was selected and compared with the currently established models (Alexnet, Squeezenet, Googlenet, Resnet50).…”

Flowchart of SIMPLE algorithm and PISO algorithm. by Feng Gao (3548)

“…Results show that under the comprehensive consideration of calculation accuracy, calculation time and memory occupancy, using sinusoidal expiratory boundary conditions combined with the PISO algorithm, with the RNG <i>k-ε</i> model during expiratory phase, and switching into the laminar flow during inspiratory phase, is the optimal strategy of simulating human breathing.…”

Flow chart of density peak clustering algorithm. by Ning Zhao (84707)

“…<div><p>In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data clustering algorithms. This paper introduces a novel higher-order hybrid clustering algorithm that combines density values and the particle swarm optimization (PSO) algorithm. …”

Schematic diagram of cluster centers in Phase 1. by Yingbo Mao (22522192)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Calibration curves for the test set of four models. by Meng Cao (105914)

Subjects:

ROC curves for the test set of four models. by Meng Cao (105914)

Subjects:

Performance metrics of the models on the training and test set. by Meng Cao (105914)

Subjects:

Compare algorithm parameter settings. by Qingwen Meng (156386)

“…<div><p>This study develops an enhanced Secretary Bird Optimization Algorithm (ASBOA) based on the original Secretary Bird Optimization Algorithm (SBOA), aiming to further improve the solution accuracy and convergence speed for wireless sensor network (WSN) deployment and engineering optimization problems. …”

Results of ablation experiment. by Ning Zhao (84707)

“…<div><p>In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data clustering algorithms. This paper introduces a novel higher-order hybrid clustering algorithm that combines density values and the particle swarm optimization (PSO) algorithm. …”

Model frame drawing. by Ning Zhao (84707)

“…<div><p>In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data clustering algorithms. This paper introduces a novel higher-order hybrid clustering algorithm that combines density values and the particle swarm optimization (PSO) algorithm. …”

Training process. by Ning Zhao (84707)

“…<div><p>In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data clustering algorithms. This paper introduces a novel higher-order hybrid clustering algorithm that combines density values and the particle swarm optimization (PSO) algorithm. …”

Data set parameters. by Ning Zhao (84707)

“…<div><p>In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data clustering algorithms. This paper introduces a novel higher-order hybrid clustering algorithm that combines density values and the particle swarm optimization (PSO) algorithm. …”

Weighted covariance matrix based GEDM model. by Ning Zhao (84707)

“…<div><p>In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data clustering algorithms. This paper introduces a novel higher-order hybrid clustering algorithm that combines density values and the particle swarm optimization (PSO) algorithm. …”

Proposed architecture testing phase. by Yasir Khan Jadoon (21433231)

“…The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. The trained model is employed in the testing phase for the feature extraction from the self-attention layer and passed to the shallow wide neural network classifier for the final classification. …”

Case 1 (100 × 20). by Rutinaldo Aguiar Nascimento (14259594)

Case 1 (100 × 20). by Rutinaldo Aguiar Nascimento (14259594)