URI | http://purl.tuc.gr/dl/dias/1FA4C9A6-4931-4606-901C-F7E43F935E59 | - |
Γλώσσα | en | - |
Τίτλος | Mining aberrant driving behavior characteristics | el |
Δημιουργός | Moustakis Vasilis | en |
Δημιουργός | Μουστακης Βασιλης | el |
Δημιουργός | Tsironis Loukas | en |
Δημιουργός | Τσιρωνης Λουκας | el |
Δημιουργός | Kontogiannis Thomas | en |
Δημιουργός | Κοντογιαννης Θωμας | el |
Δημιουργός | H. Mavropoulos | en |
Περίληψη | This article demonstrates the contribution of machine learning in modeling
of aberrant driving characteristics. We demonstrate how machine learning can be
deployed to identify, classify, and model interesting and useful knowledge patterns,
which are hidden in self reported replies to a Driving Behavior Questionnaire.
Demonstration is based on empirical results drawn from 1453 responders in Greece.
Experimentation was based on two machine learning approaches: decision tree
learning and association rule mining and learning focused on the exact driver
characteristics thought to be responsible for an accident to occur. Accuracy of results
was assessed using randomized testing | en |
Τύπος | Σύντομη Δημοσίευση σε Συνέδριο | el |
Τύπος | Conference Short Paper | en |
Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
Ημερομηνία | 2015-11-05 | - |
Ημερομηνία Δημοσίευσης | 2005 | - |
Βιβλιογραφική Αναφορά | L. Tsironis, H. Mavropoulos, V. Moustakis, T. Kontogiannis, "Mining
Aberrant Driving Behavior Characteristics, WSEAS Transactions on Information
Science and Applications," στο διεθνές συνέδριο WSEAS, Κέρκυρα, Ελλάδα, 2005. | el |