Sentence examples for abrupt data from inspiring English sources

In this study, we propose a new parameterization method which aims to improve the wiggle deviation of the interpolation, especially when interpolating the abrupt data interpolation.

First, due to the assumption of a smooth trend over time the method cannot distinguish true abrupt changes in the trend and abrupt data production changes (Rey et al. 2011).

Next to the application to earlier ICD revisions, however, the method can be extended as well with an automatic detection method for breaks in order to find these incidental coding changes (Harvey and Koopman 1992) or abrupt data production changes like the move from manual to automated coding (Rey et al. 2011).

ETS is highly adaptable to abrupt emergency data and supports high QoS and reliability.

As a result, the proposed method has fewer wiggles than the centripetal method and other methods in the cases of abrupt-changing data.

We look for similarities, point of abrupt changes, normalized data, return, volatility, graph, pure and noise part, correlation lengths, and signal-to-noise ratio.

The ordering state is the initial state of the UbiSOM algorithm and to where it possibly reverts if it can not recover from an abrupt change in the data stream.

For the case of the synthetic datasets, we use an unknown label dataset which was introduced earlier as the seed for creating three classes of data including abrupt, gradual and non-evolving.

In this paper, we adapt the improved method in hierarchy construction and experts' opinions integration, some parameters at the bottom justly in the traditional hierarchy are studied as criterion layer in improved AHP, the rationality of the method and the effect of abrupt change with the data are verified.

The abrupt edge in the data introduced by this procedure was smoothed to zero using a Gaussian fall off.

Gaussian filtering smooths out abrupt jumps within the data, thereby helping to reduce spurious results in the following steps.