Study of optimization of an LCD light guide plate with neural network and genetic algorithm.
This paper proposes an optimization method for designing a prism-pattern LCD light guide plate (LGP) using a neural-network optical model and a real-valued genetic algorithm to achieve excellent luminance uniformity in the exiting light. This newly developed method is proposed as a way of solving the complicated optimization work for non-image optics due to the numbers of ray tracing. First, a neural-network optical model is based on a back-propagation neural network. Then the neural-network optical model is incorporated into a real-valued genetic algorithm to optimize the distribution density of the prism pattern. The results show that the 13-point luminance uniformity reaches an outstanding 92.09%.
Li
Chen-Jung
CJ
Department of Mechanical and Automation Engineering, National Kaohsiung First University of Science and Technology, Nanzih District, Kaohsiung City, Taiwan. cjli@ccms.nkfust.edu.tw
Fang
Yi-Chin
YC
Cheng
Ming-Chia
MC
D000465:Algorithms; D016288:Computer Terminals; D017076:Computer-Aided Design; D004867:Equipment Design; D019544:Equipment Failure Analysis; D008029:Lighting / Q000379:methods*; D050866:Liquid Crystals; D016571:Neural Networks, Computer