Radial Basis Function Neural Network With Dynamic Optimal Learning Rate & Genetic Algorithm
نویسنده
چکیده
This paper presents a training method for radial basis function neural network (RBFNN) based on GA and dynamic optimal learning rate. Genetic algorithm (GA) is applied to search for the optimal centers from input space of the RBF. Dynamic optimal learning rate approach is also appended to the genetic algorithms’ searching procession to obtain a set of weighting factors so that the network actual output converges to the designed signal. Simulation results have revealed that the good performance of the proposed scheme. Key-Words: Neural network, Radial Basis Function, Learning rate, Genetic Algorithm
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