Accuracy Assessment of Images Classification Using RBF with Multi-swarm Optimization Methodology

  • G. Shyama Chandra Prasad
  • A. Govardhan
  • T. V. Rao
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)


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.


Multi-swarm optimization Radial basis function network Neural network Pattern recognition 


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Copyright information

© Springer India 2016

Authors and Affiliations

  • G. Shyama Chandra Prasad
    • 1
  • A. Govardhan
    • 2
  • T. V. Rao
    • 3
  1. 1.Matrusri Engineering CollegeHyderabadIndia
  2. 2.School of Information TechnologyJNTUHKukatpallyIndia
  3. 3.P.V.P. Siddhartha Engineering CollegeVijayawadaIndia

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