Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dynamic Time Scan Forecasting   The dynamic time scan forecasting method relies on the premise that the most
important pattern in a time series precedes the forecasting window, i.e., the
last observed values. Thus, a scan procedure is applied to identify similar
patterns, or best matches, throughout the time series. As oppose to euclidean
distance, or any distance function, a similarity function is dynamically
estimated in order to match previous values to the last observed values.
Goodness-of-fit statistics are used to find the best matches. Using the
respective similarity functions, the observed values proceeding the best
matches are used to create a forecasting pattern, as well as forecasting
intervals. Remarkably, the proposed method outperformed statistical and machine
learning approaches in a real case wind speed forecasting problem.

2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
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
1
The categories of this paper are: cs
11
The categories of this paper are: hep-lat