Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Construction of low-dimensional system reproducing low-Reynolds-number
  turbulence by machine learning   In a dissipative system, there exists the (global) attractor which has finite
fractal dimensions. The flow on the attractor can be parametrized by a finite
number of parameters (Temmam 1987). Using machine learning we demonstrate how
to construct precise low-dimensional governing equations which are valid in
some range of Reynolds number for low-Reynolds-number turbulence in plane
Couette flow.

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The categories of this paper are: cmp-lg
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The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th
2
The categories of this paper are: math
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
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The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
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The categories of this paper are: supr-con
1
The categories of this paper are: cs
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
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The categories of this paper are: comp-gas
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The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
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The categories of this paper are: q-alg