Abstract
Damage alarm is an important step among structure damage identification. Its objective is to evaluate the structure health. The existing damage alarm methods are mostly based on Back-Propagation Neural Networks without thinking over testing noise. Therefore, in order to avoid the disadvantages of conventional Back-Propagation Neural Networks, a modified Back-Propagation Neural Networks was proposed for structure damage alarm system in this paper. The experiment results of steel truss girder bridge show that the improved method is better than BPNN for structural damage alarm.
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Dong, X. (2011). Structural Damage Alarm Utilizing Modified Back-Propagation Neural Networks. In: Chen, R. (eds) Intelligent Computing and Information Science. ICICIS 2011. Communications in Computer and Information Science, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18134-4_44
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DOI: https://doi.org/10.1007/978-3-642-18134-4_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18133-7
Online ISBN: 978-3-642-18134-4
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