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Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective

  • Published:2020 Issue: Volume: Page:1-1
  • ISSN:1041-4347
  • Container-title:IEEE Transactions on Knowledge and Data Engineering
  • language:
  • Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Zhou Zhengyang,Wang Yang,Xie Xike,Chen Lianliang,Zhu Chaochao

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Anhui Science Foundation for Distinguished Young Scholars

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Cited by 32 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Personalized Federated Continual Learning via Multi-Granularity Prompt;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Weather Knows What Will Occur: Urban Public Nuisance Events Prediction and Control with Meteorological Assistance;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. LAMD2: Enabling Economical and Green Travel for Diversified Mobility on Demand Systems;IEEE Transactions on Mobile Computing;2024-08

4. Future Navigation Demand Trends: Accurate Ride Request Forecasting Optimization Using Machine Learning;2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN);2024-07-18

5. A novel approach to traffic modelling based on road parameters, weather conditions and GPS data using feedforward neural networks;Expert Systems with Applications;2024-07
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