| Literature DB >> 26795119 |
Chunyan Wang1, Xiaofeng Shi2, Wendong Li2, Lin Wang3, Jinliang Zhang4, Chun Yang5, Zhendi Wang5.
Abstract
Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 crude oil samples from the Bohai Sea platforms of China was carried out under controlled laboratory conditions and showed that weathering had no significant effect on the CSMF spectra. While different feature extraction methods, such as PCA, PLS and Gabor wavelet analysis, were applied to extract discriminative patterns from CSMF spectra, classifications were made via SVM to compare their respective performance of oil species recognition. Ideal correct rates of oil species recognition of 100% for the different types of oil spill samples and 92% for the closely-related source oil samples were achieved by combining Gabor wavelet with SVM, which indicated its advantages to be developed to a rapid, cost-effective, and accurate forensic oil spill identification technique.Entities:
Keywords: Concentration-synchronous-matrix-fluorescence (CSMF); Gabor wavelet analysis; Oil spill; Partial least square analysis (PLS); Principle component analysis (PCA); Supported vector machine (SVM)
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Year: 2016 PMID: 26795119 DOI: 10.1016/j.marpolbul.2016.01.001
Source DB: PubMed Journal: Mar Pollut Bull ISSN: 0025-326X Impact factor: 5.553