Neural network design by using taguchi method

S. M. Yang, G. S. Lee

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)


One of the major difficulties in neural network applications is the selection of the parameters in network configuration and the coefficients in learning rule for fast convergence. This paper develops a network design by combining the Taguchi method and the back-propagation network with an adaptive learning rate for minimum training time and effective vibration suppression. Analyses and experiments show that the optimal design parameters can be determined in a systematic way thereby avoiding the lengthy trial-and-error.

Original languageEnglish
Pages (from-to)560-562
Number of pages3
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Issue number3
Publication statusPublished - 1999 Sep

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications


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