Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Time Series Fault Classification for Wave Propagation Systems with
  Sparse Fault Data   In this work Time Series Classification techniques are investigated, and
especially their applicability in applications where there are significant
differences between the individuals where data is collected, and the
individuals where the classification is evaluated. Classification methods are
applied to a fault classification case, where a key assumption is that data
from a fault free reference case for each specific individual is available. For
the investigated application, wave propagation cause almost chaotic changes of
a measured pressure signal, and physical modeling is difficult. Direct
application of One-Nearest-Neighbor Dynamic Time Warping, a common technique
for this kind of problem, and other machine learning techniques are shown to
fail for this case and new methods to improve the situation are presented. By
using relative features describing the difference from the reference case
rather than the absolute time series, improvements are made compared to
state-of-the-art time series classification algorithms.

28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
1
The categories of this paper are: cs
7
The categories of this paper are: hep-th