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A cluster analysis on road traffic accidents using genetic algorithms

Saharan, Sabariah and Baragona, Roberto (2016) A cluster analysis on road traffic accidents using genetic algorithms. In: The 4th International Conference on Mathematical Sciences, 15–17 November 2016, Palm Garden, IOI Resort, Putrajaya.

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The analysis of traffic road accidents is increasingly important because of the accidents cost and public road safety. The availability or large data sets makes the study of factors that affect the frequency and severity accidents are viable. However, the data are often highly unbalanced and overlapped. We deal with the data set of the road traffic accidents recorded in Christchurch, New Zealand, from 2000-2009 with a total of 26440 accidents. The data is in a binary set and there are 50 factors road traffic accidents with four level of severity. We used genetic algorithm for the analysis because we are in the presence of a large unbalanced data set and standard clustering like k-means algorithm may not be suitable for the task. The genetic algorithm based on clustering for unknown K, (GCUK) has been used to identify the factors associated with accidents of different levels of severity. The results provided us with an interesting insight into the relationship between factors and accidents severity level and suggest that the two main factors that contributes to fatal accidents are “Speed greater than 60 km h” and “Did not see other people until it was too late”. A comparison with the k-means algorithm and the independent component analysis is performed to validate the results.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistic
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 13 Aug 2018 03:22
Last Modified: 13 Aug 2018 03:22
URI: http://eprints.uthm.edu.my/id/eprint/9593
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