A rank reduction autoencoder combined with classification predicts numerical dispersion in automotive crash simulations more effectively than random forests when using wavelet or slope signal inputs.
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Statistical Taylor expansion models inputs as random variables to propagate uncertainties through expressions, producing path-independent means, deviations, and reliability factors via variance arithmetic.
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CRADIPOR: Crash Dispersion Predictor
A rank reduction autoencoder combined with classification predicts numerical dispersion in automotive crash simulations more effectively than random forests when using wavelet or slope signal inputs.
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Statistical Taylor Expansion: A New and Path-Independent Method for Uncertainty Analysis
Statistical Taylor expansion models inputs as random variables to propagate uncertainties through expressions, producing path-independent means, deviations, and reliability factors via variance arithmetic.