يعرض 1,201 - 1,220 نتائج من 9,456 نتيجة بحث عن 'significantly ((((((greater decrease) OR (mean decrease))) OR (we decrease))) OR (nn decrease))', وقت الاستعلام: 0.59s تنقيح النتائج
  1. 1201

    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. 1202

    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. 1203

    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. 1204

    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. 1205

    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. 1206

    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. 1207

    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. 1208

    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. 1209

    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. 1210

    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. 1211

    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. 1212

    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. 1213

    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. 1214

    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. 1215

    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. 1216

    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. 1217
  18. 1218
  19. 1219
  20. 1220