Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Measurement uncertainty evaluation in whiplash test model via neural network and support vector machine-based Monte Carlo method

14 references·3 citing·48 second hop

FromToDepth

this work references cited by second hop

References

2013Guide to the Expression of Uncertainty in Measurement2,767 cited
2003Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems2,707 cited
2006Survey of sampling-based methods for uncertainty and sensitivity analysis1,240 cited
1985Probabilistic Sensitivity Analysis Using Monte Carlo Simulation860 cited
2011A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing810 cited
2004Combining Field Data and Computer Simulations for Calibration and Prediction622 cited
2002Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos552 cited
2003Modeling Model Uncertainty198 cited
2008Evaluation of measurement uncertainty and its numerical calculation by a Monte Carlo method96 cited
2017Measurement Uncertainty Propagation in Transistor Model Parameters via Polynomial Chaos Expansion59 cited
1999A framework for assessing uncertainties in simulation predictions45 cited
2016Uncertainty analysis of a structural–acoustic problem using imprecise probabilities based on p-box representations37 cited
2017Application of Monte Carlo Method for Evaluation of Uncertainties of ITS-90 by Standard Platinum Resistance Thermometer28 cited
2009Bayesian hierarchical uncertainty quantification by structural equation modeling

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

28 cited

Cited by

2021Six sigma robust optimization method based on a pseudo single-loop strategy and RFR-DBN with insufficient samples14 cited
2026Non-intrusive smoothed stochastic finite element method with multi-source uncertainties7 cited
2021Comparison of Pseudorandom Number Generators and Their Application for Uncertainty Estimation Using Monte Carlo Simulation7 cited