Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Physics Informed Shallow Machine Learning for Wind Speed Prediction   The ability to predict wind is crucial for both energy production and weather
forecasting. Mechanistic models that form the basis of traditional forecasting
perform poorly near the ground. In this paper, we take an alternative
data-driven approach based on supervised learning. We analyze a massive dataset
of wind measured from anemometers located at 10 m height in 32 locations in two
central and north west regions of Italy (Abruzzo and Liguria). We train
supervised learning algorithms using the past history of wind to predict its
value at a future time (horizon). Using data from a single location and time
horizon we compare systematically several algorithms where we vary the
input/output variables, the memory of the input and the linear vs non-linear
learning model. We then compare performance of the best algorithms across all
locations and forecasting horizons. We find that the optimal design as well as
its performance vary with the location. We demonstrate that the presence of a
reproducible diurnal cycle provides a rationale to understand this variation.
We conclude with a systematic comparison with state of the art algorithms and
show that, when the model is accurately designed, shallow algorithms are
competitive with more complex deep architectures.

32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga