Accuracy assessment of images classification using rbf with multi-swarm optimization methodology

Abstract

Pattern recognition issues in contemporaneous applications and its performance enhancement in learning system using multi-swarm optimization radial basis function neural network is focused on in this paper. To improve efficiency of pattern recognition, multi-swarm optimization is used as the extension of the conventional radial basis function network. The extended neural modeling with radial network and with the incorporation of multi-swarm optimization has proved better accuracy than the traditional and PSO-RBF-neuro modeling. A comparative evaluation is carried out for retrieval accuracy for the developed recognition system and is evaluated for the accuracy for the pattern recognition system.