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Neural Networks Committee for Improvement of Metal’s Mechanical Properties Estimates

  • Olga A. Mishulina
  • Igor A. Kruglov
  • Murat B. Bakirov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6593)

Abstract

In this paper we discuss the problem of metal’s mechanical characteristics estimation on the basis of indentation curves. The solution of this problem makes it possible to unify computational and experimental control methods of elastic properties of materials at all stages of equipment life cycle (manufacturing, maintenance, reparation). Preliminary experiments based on data obtained by the use of finite element analysis method have proved this problem to be ill-posed and impossible to be solved by a single multilayered perceptron at the required precision level. To improve the accuracy of the estimates we propose to use a special neural net structure for the neural networks committee decision making. Experimental results have shown accuracy improvement for estimates produced by the neural networks committee and confirmed their stability.

Keywords

Neural networks committee ill-posed problem metal’s mechanical properties 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Olga A. Mishulina
    • 1
  • Igor A. Kruglov
    • 1
  • Murat B. Bakirov
    • 2
  1. 1.National nuclear research university “MEPhI”MoscowRussia
  2. 2.“Center of material science and resource”MoscowRussia

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