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Proceedings Paper

Identification of oil spills by near-infrared spectroscopy (NIR) and support vector machine (SVM)
Author(s): Weihong Bi; Ailing Tan; Yong Zhao; Meijing Gao
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Paper Abstract

The identification of the spilled oil is an essential and important part in the investigation and handling of oil spill accidents. The combination of near-infrared spectroscopy (NIR) and chemometrics is ideal for such a situation. NIR spectroscopy is a powerful and effective technique and qualitative information can be obtained with classification models. Support vector machines (SVM) have been introduced recently in chemometrics and have proven to be powerful in NIR spectra classification tasks, such as material identification and food discrimination. In this work, the SVM is utilized to classify near infrared spectroscopy of simulated spilled oils of gasoline, diesel fuel and kerosene on the marine. A good classification performance is obtained :the identification rate were 100%, 96% and 98% on the test sets respectively.

Paper Details

Date Published: 20 November 2009
PDF: 6 pages
Proc. SPIE 7511, 2009 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 75111R (20 November 2009); doi: 10.1117/12.838054
Show Author Affiliations
Weihong Bi, Yanshan Univ. (China)
Ailing Tan, Yanshan Univ. (China)
Yong Zhao, Yanshan Univ. (China)
Meijing Gao, Yanshan Univ. (China)


Published in SPIE Proceedings Vol. 7511:
2009 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems

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