The determination of serum cholesterol concentration with improved differential evolution algorithm based on ultraviolet-visible absorption spectrum

DOI

10.2991/icmmita-16.2016.57How to use a DOI?

Keywords

Cholesterol; ultraviolet-visible absorption spectrum; Partial least square; Differential evolution; Multiple correlation

Abstract

This article uses the partial least square algorithm and the improved differential evolution algorithm to preprocess the ultraviolet-visible absorption spectral data and build a model for detection of cholesterol concentration in human serum. The result indicates that the wavelet decomposition and the partial least square algorithm can effectively reduce the multiple correlation coefficients. The absorption spectrum is investigated by different basis functions with various pre-processed spectra, and produces the best result with the prediction error of 0.12mmol/L. This study shows that the ultraviolet-visible absorption spectroscopy can offer a feasible research direction for detection and quantitative analysis of cholesterol concentration.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Mingcheng Gui
AU  - Weihua Zhu
AU  - Feng Zhu
AU  - Ying Geng
AU  - Weihao Hua
AU  - Chunmei Tang
AU  - Zhimin Zhao
PY  - 2017/01
DA  - 2017/01
TI  - The determination of serum cholesterol concentration with improved differential evolution algorithm based on ultraviolet-visible absorption spectrum
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 319
EP  - 327
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.57
DO  - 10.2991/icmmita-16.2016.57
ID  - Gui2017/01
ER  -