Abstract
The emission spectra of high color rendering phosphors, mixed with the yttrium aluminium garnet, silicon based oxynitride and nitride based phosphors, were predicted by the Lambert-Beer theory and back propagation neural network (BP NN). Firstly, the modified Lambert-Beer model was used to calculate the proportional coefficient of the emission spectra of the mixed phosphors in ratios. Next, the BP NN was implemented to train and predict the proportional coefficients. Finally, the prediction of the emission spectra of the mixed phosphors was estimated and verified by the experimental measurements. The results show that the prediction error fraction of the proportional coefficients can be controlled within 5%; the predicted emission spectra by BP NN keep high agreement with the experimental measurements with lower RMSE and Δxy as 0.019 and 0.0016, respectively.
| Translated title of the contribution | Predication of Emission Spectra for Mixed Phosphors Using Lambert-Beer Theory and Artificial Neural Network |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 2393-2398 |
| Number of pages | 6 |
| Journal | Xiyou Jinshu Cailiao Yu Gongcheng/Rare Metal Materials and Engineering |
| Volume | 50 |
| Issue number | 7 |
| Publication status | Published - 2021 |
Keywords
- Artificial neural network
- Emission spectrum
- High color rendering LED
- Lambert-Beer theory
- Mixed phosphors