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driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
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Showing 101 - 120 results of 303 for search '(( binary task driven optimization algorithm ) OR ( primary data models optimization algorithm ))', query time: 0.53s Refine Results
  1. 101
    Input features.

    Input features. by Nicola Lazzarini (3528197)

    Published 2022
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  2. 102
    Most important predictive features.

    Most important predictive features. by Nicola Lazzarini (3528197)

    Published 2022
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  3. 103
    Age feature importance.

    Age feature importance. by Nicola Lazzarini (3528197)

    Published 2022
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  4. 104
    Machine learning vs. clinicians.

    Machine learning vs. clinicians. by Nicola Lazzarini (3528197)

    Published 2022
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  5. 105
    ROC curves.

    ROC curves. by Nicola Lazzarini (3528197)

    Published 2022
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  6. 106
    PR curves.

    PR curves. by Nicola Lazzarini (3528197)

    Published 2022
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  7. 107
    Overview of the cohort definition process.

    Overview of the cohort definition process. by Nicola Lazzarini (3528197)

    Published 2022
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  8. 108
    Overall Framework of the PSO-KM Model.

    Overall Framework of the PSO-KM Model. by Hongwei Yue (574068)

    Published 2025
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  9. 109
    Overall Framework of the PSO-KM Model.

    Overall Framework of the PSO-KM Model. by Hongwei Yue (574068)

    Published 2025
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  10. 110
    Comparison of the four models.

    Comparison of the four models. by Gaosha Li (20570760)

    Published 2025
    “…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”
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  11. 111
    Data_Sheet_1_Robust optimization for casualty scheduling considering injury deterioration and point-edge mixed failures in early stage of post-earthquake relief.docx

    Data_Sheet_1_Robust optimization for casualty scheduling considering injury deterioration and point-edge mixed failures in early stage of post-earthquake relief.docx by Yufeng Zhou (3702208)

    Published 2023
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  12. 112
    Predicting the Shear Viscosity of Carbonated Aqueous Amine Solutions and Their Blends by Using an Artificial Neural Network Model

    Predicting the Shear Viscosity of Carbonated Aqueous Amine Solutions and Their Blends by Using an Artificial Neural Network Model by Ali Aminian (9580734)

    Published 2020
    “…A total of 1682 amine + CO<sub>2</sub> + water viscosity data sets for primary, secondary, and tertiary amines and 220 data points for further accuracy examinations were used. …”
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  13. 113
    Table_1_Construction of a risk screening and visualization system for pulmonary nodule in physical examination population based on feature self-recognition machine learning model.XLSX

    Table_1_Construction of a risk screening and visualization system for pulmonary nodule in physical examination population based on feature self-recognition machine learning model.X... by Fang Tian (360682)

    Published 2025
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  14. 114
    primary mouse RT single cell RNA-seq

    primary mouse RT single cell RNA-seq by Mamy ANDRIANTERANAGNA (12913196)

    Published 2023
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  15. 115
    ECE6379_PSOM.zip

    ECE6379_PSOM.zip by Xingpeng Li (11825663)

    Published 2021
    “…Optimization algorithms that are commonly used to solve these problems will also be covered including linear programming, mixed-integer linear programming, Lagrange relaxation, dynamic programming, branch and bound, and duality theory.…”
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  16. 116
    Table_8_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx

    Table_8_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

    Published 2022
    “…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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  17. 117
    Table_5_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx

    Table_5_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

    Published 2022
    “…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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  18. 118
    Table_1_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx

    Table_1_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

    Published 2022
    “…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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  19. 119
    Table_9_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx

    Table_9_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

    Published 2022
    “…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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  20. 120
    Table_7_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx

    Table_7_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

    Published 2022
    “…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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