The determination of serum cholesterol concentration with improved differential evolution algorithm based on ultraviolet-visible absorption spectrum
- 10.2991/icmmita-16.2016.57How to use a DOI?
- Cholesterol; ultraviolet-visible absorption spectrum; Partial least square; Differential evolution; Multiple correlation
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.
- © 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/).
Cite this article
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 -