Knowledge discovery from road traffic accident data in Ethiopia: Data quality, ensembling and trend analysis for improving road safety

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dc.contributor.author Beshah, Tibebe
dc.contributor.author Ejigu, Dejene
dc.contributor.author Abraham, Ajith
dc.contributor.author Snášel. Václav
dc.contributor.author Krömer, Pavel
dc.date.accessioned 2012-09-07T11:23:27Z
dc.date.available 2012-09-07T11:23:27Z
dc.date.issued 2012
dc.identifier.citation Neural network world. 2012, vol. 22, issue 3, p. 215-244. cs
dc.identifier.issn 1210-0552
dc.identifier.uri http://hdl.handle.net/10084/94977
dc.description.abstract Descriptive analyses of the magnitude and situation of road safety in general and road accidents in particular is important, but understanding of data quality, factors related with dangerous situations and different interesting patterns in a data is of even greater importance. Under the umbrella of an information architecture research for road safety in developing countries, the objective of this machine learning experimental research is to explore data quality issues, analyze trends and predict the role of road users on possible injury risks. The research employed TreeNet, Classification and Adaptive Regression Trees (CART), Random Forest (RF) and hybrid ensemble approach. To identify relevant patterns and illustrate the performance of the techniques for the road safety domain, road accident data collected from Addis Ababa Traffic Office is exposed to several analyses. Empirical results illustrate that data quality is a major problem that needs architectural guideline and the prototype models could classify accidents with promising accuracy. In addition an ensemble technique proves to be better in terms of predictive accuracy in the domain under study. cs
dc.language.iso en cs
dc.publisher Akademie věd České republiky, Ústav informatiky a České vysoké učení technické v Praze, Fakulta dopravní cs
dc.relation.ispartofseries Neural network world cs
dc.relation.uri http://isda2001.softcomputing.net/nnw2012_tibebe.pdf cs
dc.subject road safety cs
dc.subject road accident cs
dc.subject CART cs
dc.subject RandomForest cs
dc.subject TreeNet cs
dc.subject data quality cs
dc.title Knowledge discovery from road traffic accident data in Ethiopia: Data quality, ensembling and trend analysis for improving road safety cs
dc.type Article cs
dc.identifier.location Není ve fondu ÚK cs
dc.type.status Peer-reviewed cs
dc.description.source Web of Science cs
dc.description.volume 22 cs
dc.description.issue 3 cs
dc.description.lastpage 244 cs
dc.description.firstpage 215 cs
dc.identifier.wos 000306821100001

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