Acta Photonica Sinica, Volume. 45, Issue 4, 423006(2016)
Study on the Reliability of White LED Using RBF Neural Network Optimization by FOA Algorithm
Fruit fly Optimization Algorithm(FOA) and Radial-based Function(RBF) neural network model was proposed for evaluating the reliability of white Light Emitting Diode(LED) chip. The failure factors of white LED such as junction temperature, color coordinate shift were selected to the neural network input. Using fruit fly algorithm to optimization RBF neural network in order to improve the precision of the output. Studies have shown that RBF neural network is successfully predicted the LED reliability decay trend, with high stability and robustness, using fruit fly algorithm to predict average error successfully reduced to 3.1%, benefit to set up reliability prediction model in the future.
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HUANG Wei-ming, WEN Shang-sheng, FU Yi. Study on the Reliability of White LED Using RBF Neural Network Optimization by FOA Algorithm[J]. Acta Photonica Sinica, 2016, 45(4): 423006
Received: Sep. 5, 2015
Accepted: --
Published Online: May. 11, 2016
The Author Email: Wei-ming HUANG (hwmscut@163.com)