#6678. A decision-tree-based algorithm for identifying the extent of structural damage in braced-frame buildings

November 2026publication date
Proposal available till 17-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Civil and Structural Engineering;
Building and Construction;
Mechanics of Materials;
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Abstract:
Rapid health assessment of essential buildings such as hospitals, fire stations, and large residential complexes is crucial after damaging earthquakes. The use of advanced technologies such as wireless sensors, learning algorithms, and signal processing methods became more attractive in such fast applications due to their higher reliabilities and efficiencies compared to the conventional visual inspection methods. This paper presents a robust post-earthquake damage detection framework for predicting the extent and location of damage occurrence in the braced-frame structures after an earthquake. To do so, features derived from acceleration response of the structure were used along with a classification learner to determine the health condition of the structure. Decision tree classifiers are used for the purpose of damage classification where the Bayesian optimization algorithm is implemented to optimize the architecture of the mentioned classifier.
Keywords:
braced-frame building; classification; damage detection; decision tree; feature extraction; structural health monitoring

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