Laser & Optoelectronics Progress, Volume. 57, Issue 20, 203001(2020)
Application of Kernel Extreme Learning Machine and Laser Induction Fluorescence Technique in Edible Oil Identification
[5] Bi X, Jin Y B, Li S F et al. Rapid and sensitive determination of fatty acids in edible oil by liquid chromatography-electrospray ionization tandem mass spectrometry[J]. Science China Chemistry, 57, 447-452(2014).
[6] Chen Y, Luo Q S, Wang J et al. Rapid identification and characterization of recovered edible oil, based on Raman and near-infrared spectroscopy[C]//Proceedings of the 2018 3rd International Conference on Modelling. Paris,, 4(2018).
[11] Wang Y, Zhou M R, Yan P C et al. A rapid identification model of mine water inrush based on extreme learning machine[J]. Journal of China Coal Society, 42, 2427-2432(2017).
[13] Mirjalili S. Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm[J]. Knowledge-Based Systems, 89, 228-249(2015).
[14] Deng C W, Huang G B, Xu J et al. Extreme learning machines: new trends and applications[J]. Science China Information Sciences, 58, 1-16(2015).
Get Citation
Copy Citation Text
Mengran Zhou, Jinguo Wang, Hongping Song, Feng Hu, Wenhao Lai, Kai Bian. Application of Kernel Extreme Learning Machine and Laser Induction Fluorescence Technique in Edible Oil Identification[J]. Laser & Optoelectronics Progress, 2020, 57(20): 203001
Category: Spectroscopy
Received: Dec. 4, 2019
Accepted: Jan. 9, 2020
Published Online: Oct. 17, 2020
The Author Email: Jinguo Wang (wangjinguo1023@163.com)