Quantitative analysis of gas phase IR spectra based on extreme learning machine regression model

• Main Authors: Ouyang, Tinghui, Wang, Chongwu, Yu, Zhangjun, Stach, Robert, Mizaikoff, Boris, Liedberg, Bo, Huang, Guang-Bin, Wang, Qi-Jie
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Gas Sensing; Quantitative Spectrum Analysis
• Online Access: https://hdl.handle.net/10356/145682
• Institution: Nanyang Technological University

Advanced chemometric analysis is required for rapid and reliable determination of physical and/or chemical components in complex gas mixtures. Based on infrared (IR) spectroscopic/sensing techniques, we propose an advanced regression model based on the extreme learning machine (ELM) algorithm for qu...