Immune-based optimization of predicting neural networks

Abstract

Artificial immune systems turned out to be an interesting technique introduced into the area of soft computing. In the paper the idea of an immunological selection mechanism in the agent-based optimization of a neural network architecture is presented. General considerations are illustrated by the particular system dedicated to time-series prediction. Selected experimental results conclude the work. © Springer-Verlag Berlin Heidelberg 2005.