The Comparison of Neural Network Learning Paradigms: Backpropagation, Simulated Annealing, Genetic Algorithm, and Tabu Search

  • Chen Ming-Kuen (Industrial Engineering Department National Taipei University of Technology)
  • Published : 1998.11.01

Abstract

Artificial neural networks (ANN) have successfully applied into various areas. But, How to effectively established network is the one of the critical problem. This study will focus on this problem and try to extensively study. Firstly, four different learning algorithms ANNs were constructed. The learning algorithms include backpropagation, simulated annealing, genetic algorithm, and tabu search. The experimental results of the above four different learning algorithms were tested by statistical analysis. The training RMS, training time, and testing RMS were used as the comparison criteria.

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