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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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| URI | http://purl.tuc.gr/dl/dias/65257598-A57F-4B13-BA19-A008C433388D | - |
| Language | en | - |
| Title | Classification of gasoline samples using variable reduction and expectation-maximization methods | en |
| Creator | Pasadakis Nikos | en |
| Creator | Πασαδακης Νικος | el |
| Creator | Andreas Kardamakis | en |
| Publisher | Brill Academic Publishers | en |
| Content Summary | Gasoline classification is an important issue in environmental and forensic applications. Several categorization algorithms exist that attempt to correctly classify gasoline samples in data sets. We demonstrate a method that can improve classification performance by maximizing hit-rate without using a priori knowledge of compounds in gasoline samples. This is accomplished by using a variable reduction technique that de-clutters the data set from redundant information by minimizing multivariate structural distortion and by applying a greedy Expectation-Maximization (EM) algorithm that optimally tunes parameters of a Gaussian mixture model (GMM). These methods initially classify premium and regular gasoline samples into clusters relying on their gas chromatography-mass spectroscopy (GC-MS) spectral data and then they discriminate them into their winter and summer subgroups. Approximately 89% of the samples were correctly classified as premium or regular gasoline and 98.8% of the samples were correctly classified according to their seasonal characteristics. | en |
| Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Full Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-11-01 | - |
| Date of Publication | 2006 | - |
| Bibliographic Citation | Nikos Pasadakis and Andreas Kardamakis, “Classification of gasoline samples using variable reduction and expectation-maximization methods”, in International Conference of Computational Methods in Sciences and Engineering, Brill Academic Publishers, 2006, pp.435-437. | en |
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