Simulation Results Plot of the EMB System Response: (a) Step response curve of the EMB system; (b) Sine response curve of the EMB system; (c) Steady state error curve of the EMB sy... by Honglei Pang (22693724)

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Hyperparameter Configurations in PPO Training. by Honglei Pang (22693724)

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Main parameters of steering system. by Honglei Pang (22693724)

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HIL test results of low-adhesion road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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Co-simulation architecture. by Honglei Pang (22693724)

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Overall framework diagram of the study. by Honglei Pang (22693724)

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Braking system model. by Honglei Pang (22693724)

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Vehicle parameters. by Honglei Pang (22693724)

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HIL test results of curved road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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Comparison of average reward values in various simulation scenarios. by Honglei Pang (22693724)

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HIL test results of split-μ road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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Speed limits and gradients from RJ to WYJ. by Yunhu Huang (21402795)

“…On the basis of EITO_E, we propose EITO_P algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”

Speed limits and gradient from SJZ to XHM. by Yunhu Huang (21402795)

“…On the basis of EITO_E, we propose EITO_P algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”

Dice score for various <i>α</i> values (from the Eq 8) for the tracking of the CST and for the iFOD and PTT algorithms. by Thomas Durantel (20933812)

Parameter settings for metaheuristic algorithms. by Junhao Wei (6816803)

“…<div><p>Whale Optimization Algorithm (WOA) suffers from issues such as premature convergence, low population diversity in the later stages of iteration, slow convergence rate, low convergence accuracy, and an imbalance between exploration and exploitation. …”

PFC value of algorithms on two datasets. by Xing Chen (140292)

“…<div><p>In daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. …”

Results from the performance-based assessments of hand function for PALS and the age/sex matched healthy subgroup. by Conor D. Hayden (20855587)

Loss function and accuracy curve comparison. by Dayu Zhang (710629)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

The algorithm is designed to identify patterns in the treatment dataset. by Belén Otero-Carrasco (21262360)

“…<p>This process involves two key functions. First, from lines 1 to 8, the algorithm identifies amino acids that meet the occurrence threshold, starting with patterns of length 1. …”