بدائل البحث:
larger decrease » marked decrease (توسيع البحث)
we decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), teer decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), gy decreased (توسيع البحث)
larger decrease » marked decrease (توسيع البحث)
we decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), teer decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), gy decreased (توسيع البحث)
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1001
Fitting surface parameters.
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. …"
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1002
Model generalisation validation error analysis.
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. …"
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1003
Empirical model prediction error analysis.
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. …"
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1004
Fitting curve parameters.
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. …"
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1005
Test instrument.
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. …"
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1006
Empirical model establishment process.
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. …"
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1007
Model prediction error trend chart.
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. …"
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1008
Basic physical parameters of red clay.
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. …"
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1009
BP neural network structure diagram.
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. …"
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1010
Structure diagram of GBDT model.
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. …"
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1011
Model prediction error analysis index.
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. …"
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1012
Fitting curve parameter table.
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. …"
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1013
Model prediction error analysis.
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. …"
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1014
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1015
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1016
<i>SLC2A2</i> is essential for liver differentiation in developing vertebrates
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. …"
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1017
Datasets used in the study.
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. …"
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1018
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1019
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1020