Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Forecasting Brazilian and American COVID-19 cases based on artificial
  intelligence coupled with climatic exogenous variables   The novel coronavirus disease (COVID-19) is a public health problem once
according to the World Health Organization up to June 10th, 2020, more than 7.1
million people were infected, and more than 400 thousand have died worldwide.
In the current scenario, the Brazil and the United States of America present a
high daily incidence of new cases and deaths. It is important to forecast the
number of new cases in a time window of one week, once this can help the public
health system developing strategic planning to deals with the COVID-19. In this
paper, Bayesian regression neural network, cubist regression, k-nearest
neighbors, quantile random forest, and support vector regression, are used
stand-alone, and coupled with the recent pre-processing variational mode
decomposition (VMD) employed to decompose the time series into several
intrinsic mode functions. All Artificial Intelligence techniques are evaluated
in the task of time-series forecasting with one, three, and six-days-ahead the
cumulative COVID-19 cases in five Brazilian and American states up to April
28th, 2020. Previous cumulative COVID-19 cases and exogenous variables as daily
temperature and precipitation were employed as inputs for all forecasting
models. The hybridization of VMD outperformed single forecasting models
regarding the accuracy, specifically when the horizon is six-days-ahead,
achieving better accuracy in 70% of the cases. Regarding the exogenous
variables, the importance ranking as predictor variables is past cases,
temperature, and precipitation. Due to the efficiency of evaluated models to
forecasting cumulative COVID-19 cases up to six-days-ahead, the adopted models
can be recommended as a promising models for forecasting and be used to assist
in the development of public policies to mitigate the effects of COVID-19
outbreak.

2
The categories of this paper are: math
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
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The categories of this paper are: nucl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: stat
5
The categories of this paper are: gr-qc