Back-propagation neural net using Taguchi quality

Mo Chung Lee; M. S. Young; B. Hung; Rwei-Ping Ma; Chii-Maw Uang

doi:10.1117/12.363943

20 September 1999 Back-propagation neural net using Taguchi quality

Mo Chung Lee, M. S. Young, B. Hung, Rwei-Ping Ma, Chii-Maw Uang

Proceedings Volume 3801, Photorefractive Fiber and Crystal Devices: Materials, Optical Properties, and Applications V; (1999) https://doi.org/10.1117/12.363943
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

In this paper, the Taguchi Quality Engineering Method (TQEM) is applied to choose the required flight parameters in a back propagation neural algorithm for the analysis of aircraft wing loading. The screening out unwanted parameters is an important procedure in strain measurement, as using too many flight parameters increases the complexity of the network structure and also the difficulty of the learning scheme. The demonstrated results show that TQEM is easier and more reliable than traditional methods for choosing the required parameters for system identification.

Citation Download Citation

Mo Chung Lee, M. S. Young, B. Hung, Rwei-Ping Ma, and Chii-Maw Uang "Back-propagation neural net using Taguchi quality", Proc. SPIE 3801, Photorefractive Fiber and Crystal Devices: Materials, Optical Properties, and Applications V, (20 September 1999); https://doi.org/10.1117/12.363943

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