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- W4386804941 abstract "Traffic Road accidents have always been a significant cause of death in the Country. Many solutions have been developed over the years to reduce the problem of traffic and road accidents, but not much success has been achieved. Several research works have been done in the field of road accidents, which only aim at identifying the problem but not at improving the situation. The proposed research aims to resolve this problem by providing a solution that will apprise the driver about accident-prone hotspots by analyzing the severity level of locations and reducing the number of casualties. The accident dataset of the US from 2016 to 2020 from Kaggle.com is used to identify hotspot locations using a different clustering algorithm. Four clustering algorithms are applied to determine the hotspots clusters and evaluated using the Davis-Bouldin index score. Affinity propagation is preferred and achieves the best results in hotspot clustering." @default.
- W4386804941 created "2023-09-17" @default.
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- W4386804941 date "2023-01-01" @default.
- W4386804941 modified "2023-09-27" @default.
- W4386804941 title "Accident Hotspot Identification by Affinity Propagation and Compared With Different Clustering Algorithms" @default.
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- W4386804941 doi "https://doi.org/10.1007/978-981-99-3716-5_17" @default.
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