Sentence examples for stochastic testing from inspiring English sources

The validity of the simulated results was verified by stochastic testing and measured data.

Some studies have been made using a stochastic test on the statistical analysis of the GPS TEC temporal and spatial variations, and the reliability of seismic-ionospheric anomalies has been improved (Liu et al., 2010; Xia et al., 2011).

The article describes theoretical background and practical results of Analog-to-Digital Convertest (ADC) stochastic test method "Multi-Gauss" that has been designed, developed and verified at the Department of Measurement of the Czech Technical University, FEE in Prague.

Our results show that the effectiveness of the stochastic methods tested depends on the stopping criterion.

Based on the characterizations of the identified sets, we provide an inference procedure that is shown to yield valid confidence sets based on inverting stochastic dominance tests.

Results from sinusoidal and stochastic (turbulent) test flow fields show that the Taylor expansion scheme is widely applicable and highly accurate for the velocity and first derivatives.

We illustrate some of the concepts and outstanding issues for a new methodology that blends robust nonadaptive mixed μ-synthesis and stochastic hypothesis-testing concepts leading to the so-called RMMAC architecture.

Finally, a stochastic ordering test showed an alignment between the GDs who attributed higher relevance to information and communication technologies and advanced technologies for sustainability and the adoption of formal sustainability strategy.

Our results show that the effectiveness of the stochastic methods tested depends on the stopping criterion, the type of decision variables, and the use of local optimization for intensification stage.

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling.

Historically, because RCF is a stochastic process, extensive testing with subsequent statistical analysis is required to calibrate models that enable confident prediction of expected bearing service life.