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Most of the small and medium-sized backlight modules are applied to a small amount of various products.
Since the time to design a product is rigid and the light guide plate (LGP) is the key component that affects the quality of
backlight modules, photovoltaic industries can enhance the core competence if they are able to develop high standard light
guide plates with fast and efficient methods. The study proposes an optical optimal design system of light guide plate
(LGP). The optimization design is conducted in the longitudinal structure of the LGP incidence plane with three LED
light sources. Taguchi method is also used in carrying out the design of experiment through the TracePro, optical analysis
software, and the experiment data which are employed as the back-propagation neural network (BPNN) training and
testing samples and, then, created an optical quality predictor of the longitudinal structure. BPNN can predict the impact
of incidence plane luminance versus the different constructed parameters. Finally, the optical quality predictor can
effectively generate the optimal parameters settings combined with genetic algorithm (GA). The simulation results show
that the proposed system can improve the non-uniformity problem of the incidence plane but also make it easier to design
the longitudinal structure of the incidence plane.