The paper presents the use of a self-organizing feature map (SOFM) for determining damage in reinforced concrete frames with\nshear walls. For this purpose, a concrete frame with a shear wall was subjected to nonlinear dynamic analysis. The SOFM was\noptimized using the genetic algorithm (GA) in order to determine the number of layers, number of nodes in the hidden layer,\ntransfer function type, and learning algorithm. The obtained model was compared with linear regression (LR) and nonlinear\nregression (NonLR) models and also the radial basis function (RBF) of a neural network. It was concluded that the SOFM, when\noptimized with the GA, has more strength, flexibility, and accuracy.
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