Mining traffic accident features by evolutionary fuzzy rules
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86088868" target="_blank" >RIV/61989100:27240/13:86088868 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/13:86088868
Result on the web
<a href="http://dx.doi.org/10.1109/CIVTS.2013.6612287" target="_blank" >http://dx.doi.org/10.1109/CIVTS.2013.6612287</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CIVTS.2013.6612287" target="_blank" >10.1109/CIVTS.2013.6612287</a>
Alternative languages
Result language
angličtina
Original language name
Mining traffic accident features by evolutionary fuzzy rules
Original language description
Traffic accidents represent a major problem threatening peoples lives, health, and property. Traffic behavior and driving in particular is a social and cultural phenomenon that exhibits significant differences across countries and regions. Therefore, traffic models developed in one country might not be suitable for other countries. Similarly, attributes of importance, dependencies, and patterns found in data describing traffic in one region might not be valid for other regions. All this makes traffic accident analysis and modelling a task suitable for data mining and machine learning approaches that develop models based on actual real-world data. In this study, we investigate a data set describing traffic accidents in Ethiopia and use a machine learning method based on artificial evolution and fuzzy systems to mine symbolic description of selected features of the data set.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems, CIVTS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
ISBN
978-1-4673-5913-9
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
38-43
Publisher name
IEEE
Place of publication
New York
Event location
Singapur
Event date
May 16, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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