| contributor author | S. M. Yang | |
| contributor author | G. S. Lee | |
| date accessioned | 2017-05-08T23:59:09Z | |
| date available | 2017-05-08T23:59:09Z | |
| date copyright | September, 1999 | |
| date issued | 1999 | |
| identifier issn | 0022-0434 | |
| identifier other | JDSMAA-26257#560_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/121883 | |
| description abstract | 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. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Neural Network Design by Using Taguchi Method | |
| type | Journal Paper | |
| journal volume | 121 | |
| journal issue | 3 | |
| journal title | Journal of Dynamic Systems, Measurement, and Control | |
| identifier doi | 10.1115/1.2802515 | |
| journal fristpage | 560 | |
| journal lastpage | 563 | |
| identifier eissn | 1528-9028 | |
| keywords | Design | |
| keywords | Artificial neural networks | |
| keywords | Taguchi methods | |
| keywords | Networks | |
| keywords | Errors AND Vibration suppression | |
| tree | Journal of Dynamic Systems, Measurement, and Control:;1999:;volume( 121 ):;issue: 003 | |
| contenttype | Fulltext | |