Uncertainty Analysis for Computationally Expensive Models with Multiple Outputs

Uncertainty Analysis for Computationally Expensive Models with Multiple Outputs

Bayesian MCMC calibration and uncertainty analysis for computationally expensive models is implemented using the SOARS (Statistical and Optimization Analysis using Response Surfaces) methodology. SOARS uses a radial basis function interpolator as a surrogate, also known as an emulator or meta-model, for the logarithm of the posterior density. To prevent wasteful evaluations of the expensive mod...

Regarding probabilistic analysis and computationally expensive models: necessary and required?

OBJECTIVE To assess the importance of considering decision uncertainty, the appropriateness of probabilistic sensitivity analysis (PSA), and the use of patient-level simulation (PLS) in appraisals for the National Institute for Health and Clinical Excellence (NICE). METHODS Decision-makers require estimates of decision uncertainty alongside expected net benefits (NB) of interventions. This re...

Application of Multimodal Optimization for Uncertainty Estimation of Computationally Expensive Hydrologic Models

The generalized likelihood uncertainty estimation (GLUE) framework has been widely used in hydrologic studies. However, the extensive random sampling causes a high computational burden that prohibits the efficient application of GLUE to costly distributed hydrologic models such as the soil and water assessment tool (SWAT). In this study, a multimodal optimization algorithm called isolatedspecia...

Multiple Objective Evolutionary Algorithms for Independent, Computationally Expensive Objective Evaluations

Computationally secure multiple secret sharing: models, schemes, and formal security analysis

A multi-secret sharing scheme (MSS) allows a dealer to share multiple secrets among a set of participants. in such a way a multi-secret sharing scheme (MSS) allows a dealer to share multiple secrets among a set of participants, such that any authorized subset of participants can reconstruct the secrets. Up to now, existing MSSs either require too long shares for participants to be perfect secur...