Identifying Seriousness of Car Accidents using Data Mining in Jordanian Roads
Faisal Aburub1, Wael Hadi2
1Faisal Aburub*, MIS department, University of Petra, Amman, Jordan.
2Wael Hadi, CIS department, University of Petra, Amman, Jordan.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 1220-1224 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5839018520/2020©BEIESP | DOI: 10.35940/ijrte.E5839.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Deemed as the second most common cause of death in Jordan and the second leading cause of death amongst youths and infants, traffic collisions form a serious health problem in Jordan, claiming an average of 1.25 million lives per year and gravely injuring 50 million more globally. This study purposes to explore the utilisation of data mining strategies so as to identify the seriousness of car accidents in Jordan, and then studying them further so as to pinpoint a number of features that impact car accidents.
Keywords: Data Mining, Car Accidents, Associative Classification.
Scope of the Article: Data Mining.