Sentence examples for framework for validation from inspiring English sources

These preliminary data can be used as a framework for validation at a larger scale.

This study aims to establish a numerical framework for validation of methods of quantitative analysis of non-invasive MR angiography imaging protocols such as Time-of-Flight (ToF) and Phase Contrast Angiography (PCA).

As regards improvement of data quality, one major achievement of NORMAN has been the development of a common framework for validation of chemical and biological monitoring methods a protocol which is now adopted as a Technical Specification (TS) of the European Committee for Standardization (CEN) (CEN TS 16800 2015) [34] 34].

Access to all scientific data relevant to the study at hand can also avoidrepetition of previous experiments or simulations, and can serve as a starting pointfor generating new ideas for the design of alternative new approaches ormolecular/materials systems, or can provide a framework for validation [2].

Bayarri, J. Berger, R. Paulo, J. Sacks, J. Cafeo, J. Cavendish, C. Lin, J. Tu, A framework for validation of computer models, Technometrics 49 (20072007) 138 154] develop the simulator assessment and validation engine (SAVE) method as a general framework for answering this question.

This theory framework for validation is potentially useful for the evaluation of new but also established methods of the assessment of postgraduate medical trainees.

This paper presents a coherent framework for model validation for control and for controller validation (for stability and for performance) in the context where the validated model uncertainty sets are obtained by prediction error identification methods.

This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset.

We describe a framework for model validation that involves Bayesian updates of parameters in statistical calibration and validation phases.

This paper presents a methodological framework for the validation of predictive simulations that synthesizes concepts from the fields of Conventional Model Verification and Validation, Testing of Scientific Theories, Design of Experiments, Error/Sensitivity, and Statistical Exploratory Data Analysis.

VDTN@Lab aims to provide a framework for the validation of the VDTN architecture.