Optimized Light Guide Plate Optical Brightness Parameter: Integrating Back-Propagation Neural Network (BPN) and Revised Genetic Algorithm (GA)

Abstract

The light guide plate (LGP) printing process is used to obtain the optimal optical brightness, which requires the optimization of the LGP printing process parameters. This study analyzed the optical brightness optimization parameter design. This study integrated the back-propagation neural network (BPN) and a revised genetic algorithm (GA) to identify the optimal experimental level combination of the optical brightness parameter design. The obtained optical brightness process capability C_pk by the proposed method was 1.73, which was better than the process capability C_pk of 1.65 obtained by using the Taguchi method.

Keywords:

• Back-propagation neural network
• Light guide plate
• Optical brightness optimization parameter design
• Revised genetic algorithm

Notes

Optimal parameter settings after testing are italicized.

Revised GA improvement ratio:

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