Artificial Bee Colony (ABC) Algorithm on Training Artificial Neural Networks

Abstract

In this work, performance of the artificial bee colony algorithm, a recently proposed algorithm, has been tested on training on artificial neural networks which are widely used in signal processing applications and the performance of the algorithm has been compared to differential evolution and particle swarm optimization algorithms which are also population-based algorithms. Results show that ABC algorithm outperforms the other algorithms.