Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Structural Damage Detection Using Randomized Trained Neural Networks   A computationally method on damage detection problems in structures was
conducted using neural networks. The problem that is considered in this works
consists of estimating the existence, location and extent of stiffness
reduction in structure which is indicated by the changes of the structural
static parameters such as deflection and strain. The neural network was trained
to recognize the behaviour of static parameter of the undamaged structure as
well as of the structure with various possible damage extent and location which
were modelled as random states. The proposed techniques were applied to detect
damage in a simply supported beam. The structure was analyzed using
finite-element-method (FEM) and the damage identification was conducted by a
back-propagation neural network using the change of the structural strain and
displacement. The results showed that using proposed method the strain is more
efficient for identification of damage than the displacement.

16
The categories of this paper are: stat
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an