Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimation of the parameters of an infectious disease model using neural
  networks   In this paper, we propose a realistic mathematical model taking into account
the mutual interference among the interacting populations. This model attempts
to describe the control (vaccination) function as a function of the number of
infective individuals, which is an improvement over the existing susceptible
infective epidemic models. Regarding the growth of the epidemic as a nonlinear
phenomenon we have developed a neural network architecture to estimate the
vital parameters associated with this model. This architecture is based on a
recently developed new class of neural networks known as co-operative and
supportive neural networks. The application of this architecture to the present
study involves preprocessing of the input data, and this renders an efficient
estimation of the rate of spread of the epidemic. It is observed that the
proposed new neural network outperforms a simple feed-forward neural network
and polynomial regression.

20
The categories of this paper are: acc-phys
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci