Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Short-term prediction of photovoltaic power generation using Gaussian
  process regression   Photovoltaic (PV) power is affected by weather conditions, making the power
generated from the PV systems uncertain. Solving this problem would help
improve the reliability and cost effectiveness of the grid, and could help
reduce reliance on fossil fuel plants. The present paper focuses on evaluating
predictions of the energy generated by PV systems in the United Kingdom
Gaussian process regression (GPR). Gaussian process regression is a Bayesian
non-parametric model that can provide predictions along with the uncertainty in
the predicted value, which can be very useful in applications with a high
degree of uncertainty. The model is evaluated for short-term forecasts of 48
hours against three main factors -- training period, sky area coverage and
kernel model selection -- and for very short-term forecasts of four hours
against sky area. We also compare very short-term forecasts in terms of cloud
coverage within the prediction period and only initial cloud coverage as a
predictor.

29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
36
The categories of this paper are: cmp-lg