Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: From Landscape to Portrait: A New Approach for Outlier Detection in Load
  Curve Data   In power systems, load curve data is one of the most important datasets that
are collected and retained by utilities. The quality of load curve data,
however, is hard to guarantee since the data is subject to communication
losses, meter malfunctions, and many other impacts. In this paper, a new
approach to analyzing load curve data is presented. The method adopts a new
view, termed \textit{portrait}, on the load curve data by analyzing the
periodic patterns in the data and re-organizing the data for ease of analysis.
Furthermore, we introduce algorithms to build the virtual portrait load curve
data, and demonstrate its application on load curve data cleansing. Compared to
existing regression-based methods, our method is much faster and more accurate
for both small-scale and large-scale real-world datasets.

27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
5
The categories of this paper are: gr-qc