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  • 标题:Statistical Analytical Study of Traffic Accidents and Violations in the State of Kuwait and Its Social and Economic Impact on the Kuwaiti Society
  • 本地全文:下载
  • 作者:Basel M. Al-Eideh
  • 期刊名称:American Journal of Applied Mathematics and Statistics
  • 印刷版ISSN:2328-7306
  • 电子版ISSN:2328-7292
  • 出版年度:2016
  • 卷号:4
  • 期号:2
  • 页码:24-36
  • DOI:10.12691/ajams-4-2-1
  • 出版社:Science and Education Publishing
  • 摘要:Traffic accidents and their effects become one of the most important and dangerous challenges facing the community and individuals in their daily lives in the modern age, and because of the resulting deaths, reaching nearly one million and three hundred thousand cases a year and various dangerous injuries close to the fifty million cases taking into account their different consequences on the social and economic life, this is in addition to traffic violations and their impact on traffic and community public safety. Therefore, this research aims to analytical study of traffic accidents and traffic violations committed by the driver in the State of Kuwait through the study of the number of vehicles and accidents, injuries and deaths that result from these accidents in addition to the number of violations that are continuously growing and the amounts collected from committing such violations and study the relationship between them through its adaptation to some of the different statistical models and appropriate probability distributions for forecasting the coming years. The study also aims to identify the social and economic effects on the Kuwaiti society, as well as the role of government and institutions to reduce these repeated accidents and violations through the development of laws, policies and rehabilitation programs, which include some of the behavioral aspects and the process of rehabilitation and reduce the aggravation of these dangerous phenomena and costly burdens in the human life and stability in the community enjoying traffic public safety.
  • 关键词:accidents; violations; statistical analysis; statistical and probabilistic models; predict or forecast
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