چکیده مقاله
Traffic accidents globally pose a significant public health crisis, resulting in loss of life, injuries, and substantial economic burdens Predictive analytics, combining data science and health policy, offers a solution by identifying accident factors and creating proactive safety measures to save lives This study uses machine learning to analyze traffic accident data from self report questionnaires, revealing the importance of socio economic status, psychosocial factors, and long driving hours in predicting accident occurrence The research suggests interventions targeting socio economic factors, psychological assessments and improved road safety to effectively prevent accidents
کلیدواژهها
نویسندگان
T Manouchehri
Department of Statistics, Shiraz University, Shiraz, Iran
S.T Heydari
Health Policy Research Center, Shiraz University of Medical, Shiraz, Iran
K Bagheri Lankarani
Health Policy Research Center, Shiraz University of Medical, Shiraz, Iran
R Fereidooni
Health Policy Research Center, Shiraz University of Medical, Shiraz, Iran
شیوه ارجاع
Manouchehri, T and Heydari, S.T and Bagheri Lankarani, K and Fereidooni, R,1403,Road Car Accident Prediction by Using Machine Learning Techniques,1st International Biennial Conference of Artificial Intelligence and Data Science 2024,Bushehr
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی دوسالانه هوش مصنوعی و علوم داده3 اردیبهشت 1403 · بوشهر