Design of seismic-resistant steel buildings applying artificial neural networks
Keywords:
Steel buildings, structures, artificial intelligence, artificial neural networksAbstract
This paper presents the development and validation of an Artificial Neural Network (ANN) models applied to the design of steel buildings with 3-8 stories. The research was conducted in response to the need to reduce design times in seismically active areas in northwest Mexico, where traditional methods are complex and require multiple iterations of normative parameters. Sixty-two buildings were analyzed and designed using specialized software, generating a data-base for training ten ANN models, which were later validated against the established parameters in current regulations. The results show that the ANNs achieved high levels of accuracy in predicting a significant reduction in design times without compromising safety. In particular, models trained with a larger dataset showed the best performance. It is concluded that the appli-cation of ANN constitutes a relevant innovation in structural engineering, allowing for process acceleration, resource optimization and reliability maintenance in steel building design.
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