Evaluation of an optimal design method for a multilayer perceptron by using the design of experiments

  • Authors:

  • Eiichi Inohira;Hirokazu Yokoi

  • Affiliations:

  • Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka, Japan;Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka, Japan

  • Venue:
  • Artificial Life and Robotics
  • Year:
  • 2011

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Abstract

We evaluated the performance of an optimal design method for a multilayer perceptron (MLP) by using the design of experiments (DOE). In our previous work, we proposed an optimal design method for MLPs in order to determine the optimal values of such parameters as the number of neurons in the hidden layers and the learning rates. In this article, we evaluate the performance of the proposed design method through a comparison with a genetic algorithm (GA)-based design method. We target an optimal design of MLPs with six layers. We also evaluate the proposed designed method in terms of calculating the amount of optimization. Through the above-mentioned evaluation and analysis, we aim at improving the proposed design method in order to obtain an optimal MLP with less effort.