Machine learning and silicon photonic sensor for complex chemical components determination

• Main Authors: Zhang, Hui, Karim, Muhammad Faeyz, Zheng, Shaonan, Cai, Hong, Gu, Yuandong, Chen, Shoushun, Yu, Hao, Liu, Ai Qun
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Sensors; Optical Resonators
• Online Access: https://hdl.handle.net/10356/151454
• Institution: Nanyang Technological University

We propose an integrated microring resonator sensing system based on Backward-Propagation Neural Networks (BPNN)-Adaboost algorithm to predict component fraction in binary liquid mixtures. A minimum absolute error of 0.0023 and mean squared error of 0.000345 is achieved by this training model.