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Showing 1 - 20 results of 131 for search '(( lines based robust optimization algorithm ) OR ( binary data global optimization algorithm ))', query time: 0.68s Refine Results
  1. 1
    Sensitivity values of IRBMO vs. other binary algorithms.

    Sensitivity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  2. 2
    Specificity values of IRBMO vs. other binary algorithms.

    Specificity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  3. 3
    Fitness values of IRBMO vs. other binary algorithms.

    Fitness values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  4. 4
    Number of features selected for IRBMO vs. other binary algorithms.

    Number of features selected for IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  5. 5
    Classification accuracy values of IRBMO vs. other binary algorithms.

    Classification accuracy values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  6. 6
    F-score values of IRBMO vs. other binary algorithms.

    F-score values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  7. 7
    Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF

    Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF by Maya Khatun (7437011)

    Published 2019
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  8. 8
    DMTD algorithm.

    DMTD algorithm. by Yunhu Huang (21402795)

    Published 2025
    “…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”
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  9. 9
    Optimization parameters for the three treatment plans performed for the homogeneous and heterogeneous phantoms.

    Optimization parameters for the three treatment plans performed for the homogeneous and heterogeneous phantoms. by Masashi Yagi (3186909)

    Published 2023
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  10. 10
    The Pseudo-Code of the IRBMO Algorithm.

    The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  11. 11
    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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  12. 12
    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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  13. 13
    IRBMO vs. meta-heuristic algorithms boxplot.

    IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  14. 14
    IRBMO vs. feature selection algorithm boxplot.

    IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  15. 15
    Improved LMedS-based for sag measurement accuracy of transmission lines via PSO method

    Improved LMedS-based for sag measurement accuracy of transmission lines via PSO method by Xingzhi Ren (21400870)

    Published 2025
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  16. 16
    The variation of the DVHs of dose distributions in the patient case reassessed for 28 different perturbations of beam ranges and positions in the CTV (orange) and OAR (light blue) for conventional IMCT, the range (setup) and gradient robust IMCT, and WC IMCT.

    The variation of the DVHs of dose distributions in the patient case reassessed for 28 different perturbations of beam ranges and positions in the CTV (orange) and OAR (light blue)... by Masashi Yagi (3186909)

    Published 2023
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  17. 17
    Table2_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table2_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
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  18. 18
    Table1_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table1_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
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  19. 19
    Table3_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table3_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
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  20. 20
    Table4_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table4_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
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