A proposed two-level classification approach for forensic detection of diesel adulteration using NMR spectroscopy and machine learning

Author:

Dadson J. K.,Asiedu N. Y.,Iggo J. A.,Konstantin L.,Ackora-Pra J.,Baidoo M. F.,Akoto O.

Publisher

Springer Science and Business Media LLC

Reference33 articles.

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2. Sasu DD. Available at: https://www.statista.com/statistics/1293571/petroleum-products-consumption-in-the-industry-sector-in-ghana/. 2022. Accessed 13 Apr 2023.

3. Vempatapu BP, Kanaujia PK. Monitoring petroleum fuel adulteration: a review of analytical methods. TrAC Trends Anal Chem. 2017;92:1–1.

4. Joel G, Okoro LN. Recent advances in the use of sensors and markers for fuel adulteration detection: a review. Int J Res Sci Innov. 2019;6(11):82–9.

5. Nespeca MG, Munhoz JF, Flumignan DL, de Oliveira JE. Rapid and sensitive method for detecting adulterants in gasoline using ultra-fast gas chromatography and Partial Least Square Discriminant Analysis. Fuel. 2018;215:204–11.

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