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According to maximum membership degree principle,
the five samples yield the very similar results as the
experts have given. Fuzzy-neural network, capable of
storing the experts’ concerned knowledge, is verified to
be applied to the safety assessment of suspended bridge
A Assessment Result
.Four reliability observations provides an array of data
concerned with the exterior look, the main cable
elevation, main beam elevation, the internal force of
main members and the stress. The array goes as X = [ 84,
0113, 0197, 0192, 01048, 0194, 01021 ]. The
fuzzy-neural network gives a output as Y = [ 0, 0199, 0,
0, 0 ]. The assessment result suggest Bridge A is in good
condition. An integrated assessment criterion is on the
list of Regulations of Roads and Bridges, JTG H11 –
2004. Five degrees manifest different condition of roads
and bridges. A, B, C, D, E suggest the condition going
from excellent structure to these in need of overhaul. An
82 points is generated in the light of this criterion, which
is rendered as B class, characterized by the fine structure,
good vital facilities and qualified capacity to weight. The
B class of Bridge A also is statistically likened to the
results yielded by the fuzzy-neural network.
V. CONCLUSION
A model of safety assessment to suspended bridge is
established when the seven criteria is induced as exterior
examination, tower displacement, tower stress, shape of
the stiffened girder, cable force, shape of main cable and
the tension of anchored cable. The solid assessment
procedures comes to be shaped based on the fuzzy-neural
network, which is sufficient to overcome the inadequacy
of the traditional assessment measures, as the lacking
precise results, and the dependency on the experience of
experts. The fuzzy-neural network yields a result
suggesting Bridge A is in good condition. The result is in
correspondence with that brought forth based on the
criteria of Regulations of Roads and Bridges, JTG H11 –
2004. The fuzzy-neural network, with a representation of
the knowledge and the intuitive insight, reduces the
human interference with the results, leading to an
objective yielding.
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