Journal of Information Systems Engineering and Management

Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms
Ricardo Gaussmann 1 * , Dennis Coelho 1, Anita Fernandes 1 2, Paul Crocker 3 4, Valderi R. Q. Leithardt 2 4 5
More Detail
1 University of the Itajai Valley, Specialization Course in Big Data, Santa Catarina, BRAZIL
2 University of the Itajaí Valley, Master in Applied Computing, Santa Catarina, BRAZIL
3 Telecommunications Institute, IT Branch, Covilha, PORTUGAL
4 Department of Informatics, University of Beira Interior, Covilha, PORTUGAL
5 COPELABS, Lusophone University of Humanities and Technologies, Lisboa, PORTUGAL
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2020 - Volume 5 Issue 3, Article No: em0119
https://doi.org/10.29333/jisem/8427

Published Online: 30 Jul 2020

Views: 394 | Downloads: 288

How to cite this article
APA 6th edition
In-text citation: (Gaussmann et al., 2020)
Reference: Gaussmann, R., Coelho, D., Fernandes, A., Crocker, P., & Leithardt, V. R. Q. (2020). Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms. Journal of Information Systems Engineering and Management, 5(3), em0119. https://doi.org/10.29333/jisem/8427
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Gaussmann R, Coelho D, Fernandes A, Crocker P, Leithardt VRQ. Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms. J INFORM SYSTEMS ENG. 2020;5(3):em0119. https://doi.org/10.29333/jisem/8427
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Gaussmann R, Coelho D, Fernandes A, Crocker P, Leithardt VRQ. Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms. J INFORM SYSTEMS ENG. 2020;5(3), em0119. https://doi.org/10.29333/jisem/8427
Chicago
In-text citation: (Gaussmann et al., 2020)
Reference: Gaussmann, Ricardo, Dennis Coelho, Anita Fernandes, Paul Crocker, and Valderi R. Q. Leithardt. "Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms". Journal of Information Systems Engineering and Management 2020 5 no. 3 (2020): em0119. https://doi.org/10.29333/jisem/8427
Harvard
In-text citation: (Gaussmann et al., 2020)
Reference: Gaussmann, R., Coelho, D., Fernandes, A., Crocker, P., and Leithardt, V. R. Q. (2020). Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms. Journal of Information Systems Engineering and Management, 5(3), em0119. https://doi.org/10.29333/jisem/8427
MLA
In-text citation: (Gaussmann et al., 2020)
Reference: Gaussmann, Ricardo et al. "Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms". Journal of Information Systems Engineering and Management, vol. 5, no. 3, 2020, em0119. https://doi.org/10.29333/jisem/8427
ABSTRACT
The road infrastructure is considered to be a key prerequisite of social and economic development of any country and therefore solutions that assist in the management and maintenance of this key infrastructure are important. This paper presents the application of Machine Learning algorithms, such as Multilayer Perceptron Neural Network and K-means for estimating the level of services required for highway conservation in Brazil. The data used is from the Federal District highways, recorded in the form of Service Orders in the Road Administration System, as well as the road solutions catalog elaborated from the price table of the Federal District Roads Department. A database was created containing data for routine maintenance history, road solutions catalog and price lists. The machine learning algorithms were applied and evaluated, and it was concluded that the K-means algorithm had the best performance for estimating the maintenance costs of Brazilian highways.
KEYWORDS
REFERENCES
LICENSE
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.