Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Capabilities of Deep Learning Models on Learning Physical Relationships:
  Case of Rainfall-Runoff Modeling with LSTM   This study investigates the relationships which deep learning methods can
identify between the input and output data. As a case study, rainfall-runoff
modeling in a snow-dominated watershed by means of a long- and short-term
memory (LSTM) network is selected. Daily precipitation and mean air temperature
were used as model input to estimate daily flow discharge. After model training
and verification, two experimental simulations were conducted with hypothetical
inputs instead of observed meteorological data to clarify the response of the
trained model to the inputs. The first numerical experiment showed that even
without input precipitation, the trained model generated flow discharge,
particularly winter low flow and high flow during the snow-melting period. The
effects of warmer and colder conditions on the flow discharge were also
replicated by the trained model without precipitation. Additionally, the model
reflected only 17-39% of the total precipitation mass during the snow
accumulation period in the total annual flow discharge, revealing a strong lack
of water mass conservation. The results of this study indicated that a deep
learning method may not properly learn the explicit physical relationships
between input and target variables, although they are still capable of
maintaining strong goodness-of-fit results.

11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th