• DocumentCode
    3706913
  • Title

    ANN-based classifiers automatically generated by new multi-objective bionic algorithm

  • Author

    Shakhnaz Akhmedova;Eugene Semenkin

  • Author_Institution
    Siberian State Aerospace University, Krasnoyarsk, Russian Federation
  • Volume
    1
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    310
  • Lastpage
    317
  • Abstract
    An artificial neural network (ANN) based classifier design using the modification of a meta-heuristic called Co-Operation of Biology Related Algorithms (COBRA) for solving multi-objective unconstrained problems with binary variables is presented. This modification is used for the ANN structure selection. The weight coefficients of the ANN are adjusted with the original version of COBRA. Two medical diagnostic problems, namely Breast Cancer Wisconsin and Pima Indian Diabetes, were solved with this technique. Experiments showed that both variants of COBRA demonstrate high performance and reliability in spite of the complexity of the optimization problems solved. ANN-based classifiers developed in this way outperform many alternative methods on the mentioned classification problems. The workability of the proposed meta-heuristic optimization algorithms was confirmed.
  • Keywords
    "Optimization","Sociology","Statistics","Artificial neural networks","Neurons","Classification algorithms","Algorithm design and analysis"
  • Publisher
    ieee
  • Conference_Titel
    Informatics in Control, Automation and Robotics (ICINCO), 2015 12th International Conference on
  • Type

    conf

  • Filename
    7350482