Firefly Algorithm for the RBF Network Design

摘要

The paper focuses on using the firefly algorithm for designing the radial-basis neural networks. The firefly algorithm belongs to a family of the global optimization tools. The firefly algorithm is a nature-inspired and one of the most powerful algorithms for solving the NP-hard optimization problems. In the paper the firefly algorithm is used as a tool for designing of the RBF network, including estimation of its output weights and transfer function parameters. The details of the implementation are discussed. Computational experiment has been carried-out with a view to investigate effectiveness of the discussed implementation. Experiment results have confirmed usefulness of the proposed approach. Conclusions include suggestions for future research.