Neural computing: theory and practice
Neural computing: theory and practice
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Advanced Methods in Neural Computing
Advanced Methods in Neural Computing
Learning improvement of neural networks used in structural optimization
Advances in Engineering Software
Optimum design of structures by an improved genetic algorithm using neural networks
Advances in Engineering Software - Selected papers from civil-comp 2003 and AlCivil-comp 2003
Structural damage detection using neural network with learning rate improvement
Computers and Structures
Neural network constitutive model for rate-dependent materials
Computers and Structures
Estimation of seismic-induced demands on column splices with a neural network model
Applied Soft Computing
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An efficient method is introduced to predict the time history responses of structures subject to earthquakes employing neural network techniques. In order to achieve this purpose, a new intelligent neural system (INS) is designed by combining competitive and radial basis function (RBF) neural networks. In the INS the input space is classified by a competitive neural network (CNN) based on natural frequencies of the structures. Afterward an RBF network is assigned to each class and is trained by using the data located in the class. Results of illustrative examples demonstrate high performance and computational advantages of INS comparing with the single RBF network.