Confirmation of the Effect of Simultaneous Time Series Prediction with Multiple Horizons at the Example of Electron Daily Fluence in Near-Earth Spaceстатья
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Дата последнего поиска статьи во внешних источниках: 26 декабря 2017 г.
Аннотация:It is often necessary to make time series (TS) predictions
for several values of the prediction horizon. Usually such predictions
are made in autonomous mode, i.e. separately for each horizon value.
Meanwhile, it is also possible to make simultaneous predictions for all
the desired horizons, or group prediction for several horizons at once.
In the preceding studies [1], it has been demonstrated that group determination
of parameters in solving multi-parameter inverse problem with
a multi-layer perceptron (MLP) may outperform autonomous determination
if the approximated dependences of the grouped parameters on
the input features of the problem are similar and if the sets of significant
input features largely intersect. Last year it has been demonstrated, that
the effect also holds for MLP TS prediction with multiple horizons [2].
In the present study, efficiency of group prediction of TS with MLP has
been checked at the example of TS of electron daily fluence in near-Earth
space, which is characterized by rapid degradation of prediction quality
with increasing horizon. Relativistic electrons (RE) of the outer Earth’s
radiation belt are sometimes called ”killer electrons” since they can damage
electronic components, resulting in temporary or even complete loss
of spacecraft. Daily fluence is summary daily flux of these electrons; at
geosynchronous orbit of about 35,000 km altitude it is of interest due to
the large number of satellites populating this region, and it is predictable
thanks to long TS of experimental data available.
For this problem, group prediction with average size of groups proved to
outperform autonomous and simultaneous prediction. Thus, the positive
effect of group determination of outputs in multi-output problem has
been confirmed as a property of MLP as data processing algorithm.