Sentence examples for multiple prediction errors from inspiring English sources

Instead of obtaining one prediction error for the current pixel, we calculate multiple prediction errors by designing a multi-prediction scheme.

If this is the case, the critical role of the prefrontal cortex in adaptive behaviors should be most obvious when multiple prediction errors need to be processed simultaneously.

Prefrontal cortex in particular may likely continually receive information about the current level of neural activity in target regions, and then use these afferent data to determine the extent and type of excitatory and inhibitory control needed to achieve optimal tonic activity within each of the multiple efferent prediction error systems (Fig. 5).

Step 1 Form the n-dimensional dataset E = {e 1, e 2, …, e n } of prediction errors for multiple forecast horizons or wind farms using the historical data.

In particular, this work focuses on the correlation between the GPM prediction variance and the distribution of prediction errors over multiple experimental designs, as a function of location in the input space.

Open image in new window Fig. 2 Mechanism sketch of entire modelling and simulation process Step 1 Form the n-dimensional dataset E = {e 1, e 2, …, e n } of prediction errors for multiple forecast horizons or wind farms using the historical data.

A coordinated and goal-directed set of responses to prediction errors is needed when multiple error messages are generated.

Utilizing multiple prediction models according cloud types could lower both the mean absolute error and the root mean squared error on short-term irradiance prediction.

These include: (1) a hierarchical organisation with (2) reciprocal connections between areas (conveying predictions and prediction errors) that are (3) divergent (because a cause has multiple consequences) and (4) functionally asymmetrical.

Under the asymmetric representation of positive and negative prediction errors that we have just discussed, averaging these propagating errors over multiple trials (as in Figure 1a) will lead to positive means for epochs within a trial before a reward.

Since multiple meteorological elements that have propagated from neighboring areas based on atmospheric movements are related to prediction errors in the target area, we calculated those features from observed wind velocities and merged them by using a multiple kernel algorithm.