Fuel Classification in Electronic Tax Documents

Yúri Faro Dantas de Sant’Anna, Mariana Lira de Farias, Mariana Lira de Farias, Methanias Colaço Júnior, Methanias Colaço Júnior, Daniel Dantas, Daniel Dantas, Max Rodrigues Junior

2024

Abstract

The Tax on the Circulation of Goods and Services (Imposto sobre Circulação de Mercadorias e Serviços, ICMS), a responsibility of the federative units, is the main Brazilian tax collection resource. One way to collect this tax is through a product’s weighted average price to the end consumer (preço médio ponderado ao consumidor final, PMPF) of a product. The PMPF is the only resource for charging state fees for the fuel segment, so if improperly calculated, it can lead to losses both in the collection of public funds and in the evolution of prices practiced by merchants. The objective of this work is to make a comparative analysis of classification algorithms used to calculate the PMPF of fuels in the state of Sergipe to select the most appropriate technique. This system circumvented deficiencies present in the previously applied simple random sampling methodology. The naive Bayes algorithm was considered the most effective approach due to its high accuracy and feasibility of application in a real-life scenario.

Paper Citation

in Harvard Style

Faro Dantas de Sant’Anna Y., Lira de Farias M., Colaço Júnior M., Dantas D. and Rodrigues Junior M. (2024). Fuel Classification in Electronic Tax Documents. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-684-2, SciTePress, pages 337-343. DOI: 10.5220/0012390900003654

in Bibtex Style

@conference{icpram24,
author={Yúri Faro Dantas de Sant’Anna and Mariana Lira de Farias and Methanias Colaço Júnior and Daniel Dantas and Max Rodrigues Junior},
title={Fuel Classification in Electronic Tax Documents},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2024},
pages={337-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012390900003654},
isbn={978-989-758-684-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Fuel Classification in Electronic Tax Documents
SN - 978-989-758-684-2
AU - Faro Dantas de Sant’Anna Y.
AU - Lira de Farias M.
AU - Colaço Júnior M.
AU - Dantas D.
AU - Rodrigues Junior M.
PY - 2024
SP - 337
EP - 343
DO - 10.5220/0012390900003654
PB - SciTePress