The Use of Data Mining Techniques in Analysing Traffic Accidents ( An application on Khartoum State)
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2018 by IJCTT Journal|
|Year of Publication : 2018|
|Authors : Mozamel M. Saeed|
|DOI : 10.14445/22312803/IJCTT-V62P110|
MLA Style: Mozamel M. Saeed "The Use of Data Mining Techniques in Analysing Traffic Accidents ( An application on Khartoum State)" International Journal of Computer Trends and Technology 62.1 (2018): 75-79.
APA Style:Mozamel M. Saeed (2018). The Use of Data Mining Techniques in Analysing Traffic Accidents ( An application on Khartoum State). International Journal of Computer Trends and Technology, 62(1), 75-79.
This paper presents a sample of mining algorithms in data represented in "One R, J48, Naïve Bayesian" to know its optimal which pertains to analysis of traffic accidents in Khartoum State occurring through years 2007 – 2016.It is important to note that 389931 record was analysed by the statistical reports structure to reach the mining stage in data in order to creating a mechanism that is capable of studying the elements which smartly play a significant part in traffic accidents for connection. The range of relation designation between them, and its significance in traffic accidents percentage is implemented on Weka program to apply algorithms in data and ,accordingly, the presentation of the results together with analysis since the results showed that the performance of J48 algorithm generally is of more qualifications and surpasses than the other algorithms in accidents data group. It spent 0.02 seconds and the rate of error in the sample was 0.02 through its implementation and assisted in the prediction of data. The paper concludes with the implementation of J48 classification algorithms for the production of the decision tree through Weka to the point of the existence of classification of cars` accidents which occurred according to time and harm. It also shows that the harm damage rate is of the highest reaching 301394 at the rate of 77.3%, and that 2012 and 2011 accidents were the highest of all years at the rate of 11.3%, and the rate of the lowest accidents in 2007 was 7.4%.
 World Health Organization, http://www.who.int/ar/news-room/fact-sheets/detail/road-traffic-wounds
 Road Traffic Accident Statistics available at: http://www.td.gov.hk/en/road_safety/road_traffic_acc ident_statistics/2016/index.htm.
 Sachin Kumar and Durga Toshniwal, “A data mining approach to characterize road accident locations”, J. Mod. Transport, 24(1):62–72 DOI 10.1007/s40534-016-0095-5, 2016.
 Ehab Eldebaja , "The Use of Exploration Algorithms for the Analysis of Traffic Accidents (Syria)" Tishreen University Journal for Research and Scienti fic Studies - Engineering Sciences Series Vol . ( 73) No. (2), 2105.
 Sachin Kumar and Durga Toshniwal, “A data mining framework to analyse road accident data”, Journal of Big Data 2:26 DOI 10.1186/s40537-015-0035-y, 2015.
 M. Sowmya and .P. Ponmuthuramalingam, “Analyzing the Road Traffic and Accidents with Classification Techniques”, International Journal of Computer Trends and Technology (IJCTT) – volume 5 number 4 – Nov 2013.
 S. Shanthi, “Classification of Vehicle Collision Patterns in Road Accidents using Data Mining Algorithms”, International Journal of Computer Applications (0975 – 8887) Volume 35– No.12, December 2011.
 Han, Jiawei and Kamber, Micheline.,” Data Mining: concepts and Techniques. San Fransisco”, Morgan kufman Publisher, 2006.
 Khartoum status report on road safety: time for action, 2017.
 Pasko Konjevoda and Nikola Stambuk, “Open-Source Tools for Data Mining in Social Science,” Theoretical and Methodological Approaches to Social Sciences and Knowledge Management, pp.163-176.
Traffic Accidents, Data Mining, Khartoum State, Data Mining Algorithms, classification.