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.
|頁（從 - 到）||560-562|
|期刊||Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME|
|出版狀態||Published - 1999 九月|
All Science Journal Classification (ASJC) codes