Performance enhancement of arrayed waveguide grating‐based fibre Bragg grating interrogation assisted by random forest - Zizheng Yue; Wenbo Li; Di Zheng; Changjian Xie; Wei Pan; Xihua Zou (Electronics Letters, 2023)
Abstract The random forest, a powerful machine learning algorithm, is introduced to improve the performance of silicon arrayed waveguide grating (AWG)‐based fibre Bragg grating (FBG) wavelength interrogation. The experimental results show the proposed method has high interrogation accuracy with the root mean squared error (RMSE) of 0.73 pm in the whole demodulation range.