Abstract: Prey-Predator algorithm is a new metaheuristic algorithm developed for optimization problems. It is inspired by the interaction between a predator and preys of animals in the ecosystem. In this study, researchers have used the Prey-Predator algorithm to train the radial basis function neural networks. The most important in the training is finding the parameters including the centers, the widths and the output weights. Researchers have compared the performance of the new algorithm with the genetic algorithm on a logic programming data, iris flowers data set and new thyroid data set. The sum square error function was used to evaluate the performance of the algorithms. From the computational results, researchers found that Prey-Predator algorithm is better in improving the performance of radial basis function neural.
Nawaf Hamadneh Surafel Luleseged Tilahun, Saratha Sathasivam and Ong Hong Choon , 2013. Prey-Predator Algorithm as a New Optimization Technique Using in Radial Basis Function Neural Networks. Research Journal of Applied Sciences, 8: 383-387.