作者
Julius Nyerere Odhiambo, Anthony Kibira Wanjoya, Anthony Gichuhi Waititu
发表日期
2015/5
期刊
American Journal of Theoretical and Applied Statistics
卷号
4
期号
3
页码范围
178-184
出版商
Science Publishing Group
简介
Road Traffic Accident (RTA) injuries, is a neglected cause of death and disability in Nairobi County. Nairobi County has the highest number of injury rates in Kenya, notably in the active age group of (15-29) years that constitutes approximately 40% of its population. This signifies the importance of properly analyzing traffic accident data and predicting injuries, not only to explore the underlying causes of RTA injuries but also to initiate appropriate safety and policy measures in the County. Thus the study modeled RTA injuries that occurred from 2002 to 2014 in Nairobi County using the Artificial Neural Networks (ANN). ANN is a powerful technique that has demonstrated considerable success in analyzing historical data to predict future trends. However the use of ANN in accidents analysis was found to be relatively new and rare and thus the negative binomial regression approach was utilized as the study’s baseline model. The empirical study results indicated that the ANN model outperformed the negative binomial model in its overall performance.
引用总数
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学术搜索中的文章
JN Odhiambo, AK Wanjoya, AG Waititu - American Journal of Theoretical and Applied Statistics, 2015