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Attesting compliance of biodiesel quality using composition data and classification methods

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Abstract

Four methods for direct classification (decision tree classifier, K-nearest neighbors, support vector machine and artificial neural networks) have been optimized and compared to classify biodiesel samples according to their compliance to viscosity, density, oxidative stability and iodine value, having as input the composition of fatty acid methyl esters. The eight databases for the classification of each property according to the standards EN 14214, RANP 45/2014 and ASTM D6751 were increased by synthetic minority over-sampling technique to deal with imbalanced data (different numbers of compliant and non-compliant samples). Taking as criteria the best performance and lowest complexity, decision tree classifier and K-nearest neighbors methods presented the best results, ensuring maximum accuracy, sensitivity and specificity (1.0000) for samples of external validation, for almost all properties and standards. A comparison between these methods of direct classification and empirical equations (indirect classification) distinguished positively the direct classification methods in the problem addressed.

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Acknowledgements

The authors are thankful for the support received from Coordination for the Improvement of Higher Education Personnel from Brazil (CAPES), National Council for Scientific and Technological Development from Brazil (CNPq) and Foundation for Research and Scientific and Technological Development of Maranhão (FAPEMA).

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Authors and Affiliations

  1. Laboratory for Biological Information Processing, Federal University of Maranhão, São Luís, MA, 65080-805, Brazil

    Marcus Vinicius Lopes, Alex Oliveira Barradas Filho, Allan Kardec Barros & Luis Claudio O. Silva

  2. Coordination of Computer Engineering Course, Federal University of Maranhão, São Luís, MA, 65080-805, Brazil

    Alex Oliveira Barradas Filho

  3. Department of Chemistry/Chemical Technology, Federal University of Maranhão, São Luís, MA, 65080-805, Brazil

    Isabelle Moraes Amorim Viegas, Edmar Pereira Marques & Aldaléa Lopes B. Marques

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  1. Marcus Vinicius Lopes
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  2. Alex Oliveira Barradas Filho
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  3. Allan Kardec Barros
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  4. Isabelle Moraes Amorim Viegas
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  5. Luis Claudio O. Silva
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Correspondence to Alex Oliveira Barradas Filho or Allan Kardec Barros.

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Lopes, M.V., Barradas Filho, A.O., Barros, A.K. et al. Attesting compliance of biodiesel quality using composition data and classification methods. Neural Comput & Applic 31, 539–551 (2019). https://doi.org/10.1007/s00521-017-3087-4

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  • DOI: https://doi.org/10.1007/s00521-017-3087-4

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