Journal
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
Volume 26, Issue 13, Pages 1146-1153Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/15376494.2018.1430874
Keywords
Artificial intelligence techniques; artificial krill herd algorithm; artificial neural networks; krill herd; optimization; regression models; seismic reliability assessment of structures
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In this research work, the relative displacement of the stories has been determined by means of a feedforward Artificial Neural Network (ANN) model, which employs one of the novel methods for the optimization of the artificial neural network weights, namely the krill herd algorithm. For the purpose of this work, the area, elasticity, and load parameters were the input parameters and the relative displacement of the stories was the output parameter. To assess the precision of the feedforward (FF) model optimized using the Krill Herd Optimization (FF-KH) algorithm, comparison of results has been performed relative to the results obtained by the linear regression model, the Genetic Algorithm (GA), and the back propagation neural network model. The comparison of results has been carried out in the training and test phases. It has been revealed that the artificial neural network optimized with the krill herd algorithm supersedes the afore-mentioned models in potential, flexibility, and precision.
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