Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SVD-based Visualisation and Approximation for Time Series Data in Smart
  Energy Systems   Many time series in smart energy systems exhibit two different timescales. On
the one hand there are patterns linked to daily human activities. On the other
hand, there are relatively slow trends linked to seasonal variations. In this
paper we interpret these time series as matrices, to be visualized as images.
This approach has two advantages: First of all, interpreting such time series
as images enables one to visually integrate across the image and makes it
therefore easier to spot subtle or faint features. Second, the matrix
interpretation also grants elucidation of the underlying structure using
well-established matrix decomposition methods. We will illustrate both these
aspects for data obtained from the German day-ahead market.

27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th