يعرض 921 - 940 نتائج من 8,886 نتيجة بحث عن 'significantly ((((largest decrease) OR (mean decrease))) OR (we decrease))', وقت الاستعلام: 0.51s تنقيح النتائج
  1. 921

    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. 922

    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. 923

    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. 924

    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. 925

    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. 926

    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. 927

    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. 928

    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. 929

    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. 930

    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. 931

    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. 932

    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. 933

    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. 934

    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. 935

    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. 936

    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. 937
  18. 938
  19. 939

    <i>SLC2A2</i> is essential for liver differentiation in developing vertebrates حسب Yejin Kim (740789)

    منشور في 2025
    "…Data are represented as mean ± standard error of the mean (SEM). (G) Quantitative RT-PCR analysis was performed to evaluate the expression levels of igf1r. …"
  20. 940

    Datasets used in the study. حسب Rajon Banik (12066099)

    منشور في 2025
    "…</p><p>Conclusion</p><p>The findings indicate a significant increase in the availability of health facilities offering modern family planning services in Bangladesh; however, a slight decline has been observed in their overall mean readiness score. …"