Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Measurement-Based Robust Non-Gaussian Process Emulator Applied to
  Data-Driven Stochastic Power Flow   In this paper, we propose a robust non-Gaussian process emulator based on the
Schweppe-type generalized maximum likelihood estimator, which is trained on
metered time series of voltage phasors and power injections to perform
stochastic power flow. Power system data are often corrupted with outliers
caused by fault conditions, power outages, and extreme weather, to name a few.
The proposed emulator bounds the influence of the outliers using weights
calculated based on projection statistics, which are robust distances of the
data points associated with the rows vectors of the factor space. Specifically,
the developed estimator is robust to vertical outliers and bad leverage points
while retaining good leverage points in the measurements of the training
dataset. The proposed method is demonstrated on an unbalanced radial IEEE
33-Bus system heavily integrated with renewable energy sources.

8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
17
The categories of this paper are: q-fin