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An analysis of the most accident prone regions within the Dhaka Metropolitan Region using clustering

机译:使用聚类分析达卡大都市区内最易于达到的普通区

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摘要

Most of the world's developed countries have decreased the unusual deaths like traffic accidents of their citizens by taking efficient steps. In Bangladesh, injuries because of road accidents have become a regular incident. The highly-populated cities in Bangladesh are still having such incidents daily. As the number of vehicles is increasing and most of the drivers are not willing to follow the traffic rules, injuries due to traffic accidents are not going down at all. Among all those big cities in Bangladesh, Dhaka City has the highest amount of road accidents. So, in this paper we focus on the most hazardous regions in Dhaka Metropolitan area. We have collected the accident related data from Accident Research Institute (ARI) at Bangladesh University of Engineering and Technology (BUET) that is located in the city of Dhaka. In our paper, we have used the fuzzy C-means clustering, expectation maximisation, hierarchical agglomerative clustering and K-means clustering to identify the regions where traffic incidents occurs the most in Dhaka Metropolitan area. The missing values for some attributes in the dataset are overwritten by the mean/mode of that attribute itself.
机译:世界上大多数发达国家通过有效步骤减少了与公民交通事故中的不寻常的死亡。在孟加拉国,由于道路事故而受伤已成为常规事件。孟加拉国的高度人口稠密的城市仍然每天都有这样的事件。随着车辆的数量增加,大多数司机不愿意遵循交通规则,由于交通事故导致的伤害根本不会下降。德哈卡城的所有这些大城市中都有最多的道路事故。因此,在本文中,我们专注于达卡大都市区最危险的地区。我们在孟加拉国工程和技术(Buet)大学的事故研究所(ARI)中收集了事故研究所(ARI)的事故相关数据,位于达卡市。在我们的论文中,我们使用了模糊的C-Means聚类,期望最大化,分层凝聚聚类和K-Means Clustering,以确定Dhaka Metropolitan地区最多发生的交通事故的地区。 DataSet中某些属性的缺失值被该属性本身的均值/模式覆盖。

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