Machine learning and silicon photonic sensor for complex chemical components determination

• Main Authors: Zhang, Haochi, Muhammad Faeyz Karim, Zheng, Shaonan, Cai, H., Gu, Y. D., Chen, Shou Shun, Yu, H., Liu, Ai Qun
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Sensors; Optical Resonators
• Online Access: https://hdl.handle.net/10356/138831
• 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.