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A Novel Bayesian Model Validation Method Based on Bootstrap Resampling and Distance Remapping
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DOI：10.1016/j.ast.2025.111531.png)
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Abstract
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• A novel perspective on the classification of uncertainty is described. • Transitional Markov chains Monte Carlo method with simulated annealing is introduced for model calibration. • Bootstrap resampling and distance remapping strategies are introduced to assess the effectiveness of the model calibration and the quality of the samples. • A concentration indicator based on Kullback-Leibler divergence is proposed to quantitatively assess the credibility of calibration results.
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5.8
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AIAA JournalIF0
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SCIENTIFIC REPORTSIF3.9
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