Dataciencia

Colección SciELO Chile

A Formal Method for Driver Identification

Indexado

Scopus

SCOPUS_ID:85139176846

DOI

10.1007/978-3-031-07707-4_19

Año

2023

Tipo

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras

Abstract

This paper presents a preliminary study of the application of formal concept analysis to automatic driver identification. Specifically, a methodology based on attribute implications has been considered and its main features have been studied. From a particular dataset, the proposed methodology focuses on driver recognition by analyzing the values of a subset of variables related to driving style.

Revista

Revista	ISSN
Studies In Computational Intelligence	1860-949X

Métricas Externas

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Disciplinas de Investigación

WOS
Sin Disciplinas

Scopus
Sin Disciplinas

SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional

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Autores - Afiliación

Ord.	Autor	Género	Institución - País
1	Aragón, Roberto G.	Hombre	Universidad de Cádiz - España
2	Eugenia Cornejo, M.	-	Universidad de Cádiz - España
3	Medina, Jesús	Hombre	Universidad de Cádiz - España
4	Rubio-Manzano, Clemente	Hombre	Universidad de Cádiz - España Universidad del Bío Bío - Chile

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Financiamiento

Fuente
Universidad del Bío-Bío
European Regional Development Fund
European Cooperation in Science and Technology
Agencia Estatal de Investigación
State Research Agency

Muestra la fuente de financiamiento declarada en la publicación.

Agradecimientos

Agradecimiento
Partially supported by the 2014–2020 ERDF Operational Programme in collaboration with the State Research Agency (AEI) in project PID2019-108991GB-I00, and with the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia in project FEDER-UCA18-108612, and by the European Cooperation in Science & Technology (COST) Action CA17124. Furthermore, this work has been performed in collaboration with the research group SOMOS (SOftware-MOdelling-Science) funded by the University of Bío-Bío.

Agradecimiento

Partially supported by the 2014–2020 ERDF Operational Programme in collaboration with the State Research Agency (AEI) in project PID2019-108991GB-I00, and with the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia in project FEDER-UCA18-108612, and by the European Cooperation in Science & Technology (COST) Action CA17124. Furthermore, this work has been performed in collaboration with the research group SOMOS (SOftware-MOdelling-Science) funded by the University of Bío-Bío.