NIR Spectroscopy and NMF Algorithm for Identification of Oil Pollutants in Water

DOI

10.2991/meic-14.2014.104How to use a DOI?

Keywords

NIR Spectroscopy; Non-negative matrix factorization; oil pollutans;; Support Vector Machine; Genetic algorithm

Abstract

Oil pollutants is one of the major pollution sources in water. Accurate, rapid, and convenient detection method of oil pollutants in water has very important theoretical value and practical significance. The combination of near-infrared spectroscopy (NIR) and chemometrics is ideal for such a situation. NIR spectroscopy is a powerful and effective technique. traditional NIR methods do not take full account of the absorbance data non-negative characteristics, resulting in the analysis lack of reasonable explanation. In this paper, the qualitative discriminate method of single species oil contaminants based on non-negative matrix factorization feature extraction combined with support vector machine classification algorithm is studied. Non-negative matrix factorization algorithm and support vector machine classifier parameters on classification accuracy are discussed in depth to optimize NIR qualitative classification model. The present method has a good identification effect and strong generalization ability and can work as a new method for rapid identification of oil pollutants in water

Copyright

© 2014, 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  - Ailing Tan
AU  - Yong Zhao
AU  - Xuan Guo
PY  - 2014/11
DA  - 2014/11
TI  - NIR Spectroscopy and NMF Algorithm for Identification of Oil Pollutants in Water
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 461
EP  - 465
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.104
DO  - 10.2991/meic-14.2014.104
ID  - Tan2014/11
ER  -