Abstract
Possible yielding of the cross-section of a structure might significantly decrease the safety margin of the investigated structure. The cross-section yielding causes a change of structure stiffness and, further, dynamic characteristics. The measurement of the changes of the dynamic parameters may provide information necessary to identify the load causing yielding of the cross-section, and further the yielding index (calculated when the load causing yielding is known) enables evaluation of structure safety margin. In the paper the semi-Bayesian neural networks are utilized to solve the identification problem.
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Miller, B. (2010). Application of Semi-Bayesian Neural Networks in the Identification of Load Causing Beam Yielding. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15819-3_13
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DOI: https://doi.org/10.1007/978-3-642-15819-3_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15818-6
Online ISBN: 978-3-642-15819-3
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