A comparison between firefly and prey-predator algorithms based on artificial neural networks

Abstract

Firefly and prey-predator algorithms are nature inspired metaheuristic algorithms. Radial basis function neural network is used in solving classification problems. This paper deals with both algorithms for training radial basis function neural network. We used 10 different classification data sets to validate our tactic. These data are used in radial basis function neural network. To evaluate the performance of both algorithms, the sum of Squared Error function is used. Our simulation results show that the algorithms are suitable to use in training artificial neural networks.