يعرض 841 - 860 نتائج من 8,895 نتيجة بحث عن 'significant ((((gap decrease) OR (((we decrease) OR (teer decrease))))) OR (mean decrease))', وقت الاستعلام: 0.53s تنقيح النتائج
  1. 841

    Structure diagram of ensemble model. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  2. 842

    Fitting formula parameter table. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  3. 843

    Test plan. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  4. 844

    Fitting surface parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  5. 845

    Model generalisation validation error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  6. 846

    Empirical model prediction error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  7. 847

    Fitting curve parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  8. 848

    Test instrument. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  9. 849

    Empirical model establishment process. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  10. 850

    Model prediction error trend chart. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  11. 851

    Basic physical parameters of red clay. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  12. 852

    BP neural network structure diagram. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  13. 853

    Structure diagram of GBDT model. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  14. 854

    Model prediction error analysis index. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  15. 855

    Fitting curve parameter table. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  16. 856

    Model prediction error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…By developing and validating both empirical and machine learning prediction models, we unravel the evolution of thermal conductivity in response to these factors: within the range of influencing variables, thermal conductivity exhibits an exponential or linear increase with rising water content and dry density, while it decreases exponentially with increasing freeze-thaw cycles. …"
  17. 857

    Bluetooth beacons with colour coded lanyards. حسب J Mark Ansermino (13958512)

    منشور في 2025
    "…During the baseline period, the time to antimicrobials decreased significantly in Kenya (132 and 58 minutes) at control and intervention sites. …"
  18. 858

    Table 1_United States military working dogs from 2019 to 2021: analysis of causes of service discharge and decreased service life.docx حسب Dakota Discepolo (16804191)

    منشور في 2025
    "…ANOVA analysis comparing mean service life resulted in significant differences of mean overall service with main effects of breed (p = 0.0252), outcome (p = 0.0004), service discharge category (p < 0.0001), and subpopulation (p < 0.0001).…"
  19. 859
  20. 860