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S&T Best Computing Projects
Graph embeddings for predicting traffic accident black spots
/sw/zh-hans/islandora/object/stcompfyp%3A127/datastream/OBJ/view
作品集
S&T Best Computing Projects
细节
识别号
stcompfyp:127
题名
Graph embeddings for predicting traffic accident black spots
作品类型
Final Year Project/Work
系列 / 集 / 库
S&T Best Computing Projects
创建者
Lo, Ka Ho (group member)
Cheng, Wang To (group member)
Cheung, Hang Tak (group member)
Lui, Kwok Fai Andrew 呂國輝 (supervisor)
学院 / 部门
School of Science and Technology (S&T)
课程
Bachelor of Computing with Honours in Internet Technology
日期
2021
摘要
The aim of the project is to use observational data to build a deep machine learning model to model the relation between the accident proneness and road network structure design, road installations, and road local properties. In conclusion, this model provides a basis for improving the conditions of traffic facilities and enhancing traffic safety.
资料类型
PDF
语言
English
资料描述
5 pages.
奖项
1st runner-up, Final Year Project (FYP) Competition (18th), 2021 (IEEE(HK) Computational Intelligence Chapter, Institute of Electrical and Electronics Engineers Hong Kong Section)
关键词
traffic safety; computer algorithms; deep learning (machine learning)
存取限制
Public Access
固定连结
https://repository.lib.hkmu.edu.hk/sw/islandora/object/stcompfyp:127
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