Search alternatives:
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
d optimization » _ optimization (Expand Search), b optimization (Expand Search), led optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
based dose » based case (Expand Search), based dosing (Expand Search)
based d » based 3d (Expand Search), based _ (Expand Search), based 2 (Expand Search)
Showing 1 - 20 results of 130 for search '(( binary based dose optimization algorithm ) OR ( lines based d optimization algorithm ))', query time: 0.59s Refine Results
  1. 1
    PoD of cracks by ultrasonic method.

    PoD of cracks by ultrasonic method. by Dapeng Wang (250459)

    Published 2023
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  2. 2
    Greedy optimization algorithm.

    Greedy optimization algorithm. by Alexis Bénichou (19832361)

    Published 2024
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  3. 3
    Automated Discovery and Optimization of 3D Topological Photonic Crystals

    Automated Discovery and Optimization of 3D Topological Photonic Crystals by Samuel Kim (1682104)

    Published 2023
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  4. 4
    Distribution and survival based cutoff optimization for proportion of D2-40 stained sinus with respect to overall survival by “Cutoff Finder” algorithm.

    Distribution and survival based cutoff optimization for proportion of D2-40 stained sinus with respect to overall survival by “Cutoff Finder” algorithm. by Christina C. Westhoff (14498351)

    Published 2023
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  5. 5
    The <i>D</i><sub><i>98</i></sub> in the CTV and the for the nominal scenario optimized using the WC algorithm in homogeneous and heterogeneous phantom.

    The <i>D</i><sub><i>98</i></sub> in the CTV and the for the nominal scenario optimized using the WC algorithm in homogeneous and heterogeneous phantom. by Masashi Yagi (3186909)

    Published 2023
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  6. 6
    The <i>D</i><sub><i>98</i></sub> in the CTV and the for the nominal scenario optimized using the SC algorithm in homogeneous and heterogeneous phantoms.

    The <i>D</i><sub><i>98</i></sub> in the CTV and the for the nominal scenario optimized using the SC algorithm in homogeneous and heterogeneous phantoms. by Masashi Yagi (3186909)

    Published 2023
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  7. 7
    Algorithm verification.

    Algorithm verification. by Dmitrii Smirnov (8822324)

    Published 2020
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  8. 8
    Performance of optimization algorithms in six different network types.

    Performance of optimization algorithms in six different network types. by Maurits H. W. Oostenbroek (11331123)

    Published 2021
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  9. 9
    Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach

    Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

    Published 2020
    “…In this study, we considered both dataset and algorithm optimization to address the challenge of predicting OBA-related molecular properties. …”
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  10. 10
    Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach

    Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

    Published 2020
    “…In this study, we considered both dataset and algorithm optimization to address the challenge of predicting OBA-related molecular properties. …”
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  11. 11
    Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach

    Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

    Published 2020
    “…In this study, we considered both dataset and algorithm optimization to address the challenge of predicting OBA-related molecular properties. …”
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  12. 12
    Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage

    Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage by Hetao Guo (15425082)

    Published 2023
    “…We innovatively adopted the detectable IR radiation power as the optimization fitness function, based on the particle swarm optimization (PSO) algorithm, to execute powerful cooling and simultaneously minimize the emitting within the atmospheric window for enhanced camouflage. …”
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  13. 13
    Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage

    Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage by Hetao Guo (15425082)

    Published 2023
    “…We innovatively adopted the detectable IR radiation power as the optimization fitness function, based on the particle swarm optimization (PSO) algorithm, to execute powerful cooling and simultaneously minimize the emitting within the atmospheric window for enhanced camouflage. …”
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  14. 14
    Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage

    Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage by Hetao Guo (15425082)

    Published 2023
    “…We innovatively adopted the detectable IR radiation power as the optimization fitness function, based on the particle swarm optimization (PSO) algorithm, to execute powerful cooling and simultaneously minimize the emitting within the atmospheric window for enhanced camouflage. …”
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  15. 15
    Comparison of presented algorithm precision to Bot et al.

    Comparison of presented algorithm precision to Bot et al. by Dmitrii Smirnov (8822324)

    Published 2020
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  16. 16
    The <i>D</i><sub><i>98</i></sub> in the CTV and the for the nominal scenario in the patient case.

    The <i>D</i><sub><i>98</i></sub> in the CTV and the for the nominal scenario in the patient case. by Masashi Yagi (3186909)

    Published 2023
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  17. 17
    Pearson correlation coefficients of each input parameter (<i>d</i><sub><i>IX</i></sub>, <i>d</i><sub><i>CX</i></sub>, <i>d</i><sub><i>DX</i></sub>, <i>d</i><sub><i>VX</i></sub>, <i>SINR</i><sub><i>th</i></sub>, <i>P</i><sub><i>I</i></sub>) and the output (<i>P</i><sub><i>int</i></sub> and EE).

    Pearson correlation coefficients of each input parameter (<i>d</i><sub><i>IX</i></sub>, <i>d</i><sub><i>CX</i></sub>, <i>d</i><sub><i>DX</i></sub>, <i>d</i><sub><i>VX</i></sub>, <i... by Rana Ahmed (4923127)

    Published 2024
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  18. 18
    Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information.

    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)

    Published 2024
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  19. 19
    Results from trajectory optimization of walking.

    Results from trajectory optimization of walking. by Antoine Falisse (6061601)

    Published 2019
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  20. 20
    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>.

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

    Published 2021
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