Showing 1 - 20 results of 33 for search '(( algorithm learning prediction ) OR ( algorithm python function ))~', query time: 0.37s Refine Results
  1. 1

    Reward function related parameters. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  2. 2

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

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  3. 3

    EMB and SBW system structure. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  4. 4

    Raw data. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  5. 5

    Code program. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  6. 6

    The HIL simulation data flowchart. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  7. 7

    Steering system model. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  8. 8

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

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  9. 9

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

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  10. 10

    Co-simulation architecture. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  11. 11

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

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  12. 12

    Braking system model. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
  13. 13

    Vehicle parameters. by Honglei Pang (22693724)

    Published 2025
    “…Results show that, compared to Model Predictive Control (MPC) and Sliding Mode Control (SMC), the PPO algorithm reduces braking distance by 15–20% on low-adhesion roads, decreases lateral deviation by 25–30% on split-μ roads, and suppresses yaw rate oscillation by 28.8% on curved roads. …”
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    GameOfLife Prediction Dataset by David Towers (12857447)

    Published 2025
    “…This task is relatively simple for a human to do if a bit tedious, and should theoretically be simple for Machine Learning algorithms. Each cells's state is calculated based off the number of alive neighbour's in the previous step. …”
  20. 20

    Table1_Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning.pdf by Lijuan Liang (4277053)

    Published 2024
    “…We used the Covarep open-source algorithm to extract a total of 1200 high-level statistical functions for each sample. …”