Evaluation on Energy Equivalent Ductility Index Based on Optimized Algorithm

Abstract:

back propagation(BP), radial basis function(RBF) and genetic algorithmback propagation (GABP) are used to train and predict the ultimate ductility index μΔeof dualenergy equivalent method. Five control parameters and PEER database and quasistatic test are used as training and prediction samples. BP and optimization algorithm of its node numbers in hidden layer and learning rate are compiled, RBF and optimization algorithm of its node numbers and central width are compiled. Genetic algorithm (GA) is used for optimizing weight wij and threshold θj in backpropagation (BP) to inhibit the local optimum, making relationship between testing data approximate to the real mapping principle. Algorithms is realized to predict μΔe of fullscale columns. Research indicates GABP has optimal adaptability and computing superiority, provide new method for structural damage evaluation.