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- W2759922515 abstract "Data Science has burst into simulation-based en-gineering sciences with an impressive impulse. However, data are never uncertainty-free and a suitable approach is needed to face data measurement errors and their intrinsic randomness in problems with well-established physical constraints. We face this problem by hybridizing a standard mathematical modeling approach with a new data-driven solver accounting for the phenomenological part of the problem and able to handle the uncertainty of input data in an intelligent way. The reliability-based data-driven procedure performance is evaluated in a simple but illustrative unidimensional problem showing, in contrast with other data-driven solvers, better convergence, higher accuracy, clearer interpretation and major flexibility." @default.
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- W2759922515 date "2017-05-04" @default.
- W2759922515 modified "2023-09-28" @default.
- W2759922515 title "A new reliability-based data-driven approach to simulation-based models" @default.
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