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The automotive recall data search and its analysis applying machine learning.
- Source :
- Production / Produção; 2023, Vol. 33, p1-17, 17p
- Publication Year :
- 2023
-
Abstract
- Paper aims: This article investigates the worldwide trend of growth in the number of recalls, as well as in the number of products involved in each campaign. Originality: To investigate these facts, a study of the automotive recall was developed, comprising Brazil, the European Union, and the United States of America. Research method: Due to the different availabilities between the locations, search tools and software were developed to obtain and group hidden data from 2010 to 2019. Main findings: In this work, the impacts of the recall were analyzed using three categories of algorithms: clustering, classification, and regression. Analyzes were made about the results obtained and discussions were built about the importance of applying the machine learning technique. Implications for theory and practice: The use of search tools and software to obtain and group hidden data in databases and opens the opportunity for new research in various areas. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01036513
- Volume :
- 33
- Database :
- Complementary Index
- Journal :
- Production / Produção
- Publication Type :
- Academic Journal
- Accession number :
- 174590275
- Full Text :
- https://doi.org/10.1590/0103-6513.20220117