Genetic algorithm for fuel spill identification

• Published in: Analytica chimica acta Vol. 437; no. 2; pp. 233 - 246
• Main Authors: Lavine, B.K, Brzozowski, D, Moores, A.J, Davidson, C.E, Mayfield, H.T
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 27.06.2001; Elsevier
• Subjects: Analytical chemistry; Applied sciences; Chemistry; Chromatographic methods and physical methods associated with chromatography; Crude oil, natural gas and petroleum products; Energy; Exact sciences and technology; Feature selection; Fingerprint data; Fuel spill identification; Fuels; Gas chromatographic methods; Genetic algorithm; Machine learning; Pattern recognition analysis; Pollution caused by production, transportation and treatment of oil and oil shales. Water and soil pollution. Treatments. Pollution control; Pattern recognition analysis; Feature selection; Fuel spill identification; Genetic algorithm; Fingerprint data; Machine learning; Oil spill; Data analysis; Molecular structure; Evolutionary algorithm; Flame ionization detector; Pattern recognition; Multivariate analysis; Gas chromatography; Liquid fuel; Water pollution control; Environmental monitoring; Learning algorithm; Chemometrics; Principal component analysis

Gas chromatography is frequently used to fingerprint fuel spills, with the gas chromatograms of the spill sample and the different candidate fuels compared visually in order to seek a best match. However, visual analysis of gas chromatograms is subjective and is not always persuasive in a court of l...