Sentence examples for a sequential data from inspiring English sources

Both systems provide quick direct access to individual collision events in a sequential data store of several terabytes, and they both considerably improve the event analysis efficiency.

In this work, we describe a sequential data assimilation extension of LIS that incorporates multiple observational sources, land surface models and assimilation algorithms.

In this presentation I will focus on the most unique aspect of our work: adaptive scheduling of observations using the principles of Bayesian experimental design in a sequential data analysis setting.

In particular, we give a sequential data structure that uses linear space, and requires O log n) expected time and O log n) time for lookups with high probability.

In this paper, a method is proposed for the sequential reconstruction of the plume, by coupling a sequential data assimilation algorithm based on inverse modelling with an observation targeting strategy.

In a synthetic study we explore the potential of using surface soil moisture measurements obtained from different satellite platforms to retrieve soil moisture profiles and soil hydraulic properties using a sequential data assimilation procedure and a 1D mechanistic soil water model.

However, SBSE may improve on such estimates by using microarray summary statistics to direct a sequential data-driven analysis of the data that preferentially 'weights' for the most significant changes in expression.

The reservoir model is then coupled with a nonlinear sequential data assimilation scheme for tracking the fluid front dynamics to maximize the water flood sweeping efficiency by controlling the injection rates.

The Kalman filter is an optimal sequential data assimilation method for linear dynamics and measurement processes with Gaussian error statistics.

The first one is a single stream sequential data, and the second is a multi-stream one.

It is a generative representation of sequential data with an underlying markovian process selecting state-dependents distributions, from which observations are drawn.