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significant optimization » significant limitation (Expand Search), significant application (Expand Search), significant association (Expand Search)
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Showing 1 - 20 results of 33 for search '(( significant ((main decrease) OR (mean decrease)) ) OR ( significant optimization methods ))~', query time: 0.41s Refine Results
  1. 1
    Mean TTC under different weights.

    Mean TTC under different weights. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  2. 2
    SD and mean TTC under different weights.

    SD and mean TTC under different weights. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  3. 3
    Snake optimizer algorithm optimization process.

    Snake optimizer algorithm optimization process. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  4. 4
    The main notations used in this paper.

    The main notations used in this paper. by Bin Zhao (276445)

    Published 2025
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  5. 5
    SD under different weights.

    SD under different weights. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  6. 6
    Model framework.

    Model framework. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  7. 7
    Vehicle travel time.

    Vehicle travel time. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  8. 8
    SD under different penetration rates.

    SD under different penetration rates. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  9. 9
    Notation description.

    Notation description. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  10. 10
    Five-stage speed adjustment.

    Five-stage speed adjustment. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  11. 11
    Parameter values.

    Parameter values. by Jianrong Cai (14245136)

    Published 2024
    “…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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  12. 12
    Process of UWB location prediction based on LSTM.

    Process of UWB location prediction based on LSTM. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  13. 13
    Time of flight ranging model.

    Time of flight ranging model. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  14. 14
    Localization trajectory for experiment 2.

    Localization trajectory for experiment 2. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  15. 15
    Crane experimental platform.

    Crane experimental platform. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  16. 16
    Localization trajectory for experiment 1.

    Localization trajectory for experiment 1. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  17. 17
    SO-LSTM loss value curve.

    SO-LSTM loss value curve. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  18. 18
    UWB data grouping.

    UWB data grouping. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  19. 19
    Network model and time slot allocation.

    Network model and time slot allocation. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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  20. 20
    SO-LSTM algorithm parameters.

    SO-LSTM algorithm parameters. by Li Wang (15202)

    Published 2023
    “…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”
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