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

Title:

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

Creator:

Beshah, Tibebe, Ejigu, Dejene, Abraham, Ajith, Krömer, Pavel, and Snášel, Václav

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:5ebf455c-a195-41b8-ae19-2d2a3e933afb
uuid:5ebf455c-a195-41b8-ae19-2d2a3e933afb
doi:10.14311/NNW.2012.22.013

Subject:

Road safety, road accident, CART, RandomForest, TreeNet, and data quality

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

Descriptive analysis 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 various interesting patterns in data is of even greater importance. Under the umbrella of 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 subject 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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2012 Volume:22 | Number:3

Harvested from:

CDK

Metadata only:

false