Discovering associated factors behind road accidents using association rule mining: A case study from Gujarat, Pakistan
1 Department of Computer Science & Information Technology, University of Lahore, Gujarat, Pakistan.
2 Department of Computer Science and Engineering, University of Hafr Al-Batin, Saudi Arabia.
Case Study
World Journal of Advanced Research and Reviews, 2022, 15(03), 001–011
Article DOI: 10.30574/wjarr.2022.15.3.0885
Publication history:
Received on 28 July 2022; revised on 30 August 2022; accepted on 01 September 2022
Abstract:
Traffic and road safety is an international issue that is among the major concerns of the respective governing bodies around the world. Regulations and restrictions surrounding this issue can be legislated and applied only after identifying and understanding the numerous factors and conditions that increase the likelihood of traffic accidents. In this research work, we study and analyze the road accidents data and figure out the major factors that contribute to these incidents. The data was collected from Gujrat rescue office and outstanding results are achieved by applying association rules mining using Apriori algorithm. Our research and analysis found that some factors are greater contributors than others and need careful enforced legislation. Other researchers have also used the Apriori algorithm to analyze traffic accidents data from their regions and like our experience this algorithm has produced accurate and effective results. We also try to provide additional insights through visualization that may serve as guidelines to regulate better traffic control systems
Keywords:
Data mining; Apriori algorithm; Association rule mining; Traffic accidents analysis
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Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0