Event prediction in the big data era: A systematic survey
L Zhao - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …
either our society or the nature, such as earthquakes, civil unrest, system failures …
A review of incident prediction, resource allocation, and dispatch models for emergency management
In the last fifty years, researchers have developed statistical, data-driven, analytical, and
algorithmic approaches for designing and improving emergency response management …
algorithmic approaches for designing and improving emergency response management …
Real-time traffic accidents post-impact prediction: Based on crowdsourcing data
Traffic accident management is a critical issue for advanced intelligent traffic management.
The increasingly abundant crowdsourcing data and floating car data provide new support for …
The increasingly abundant crowdsourcing data and floating car data provide new support for …
Spatiotemporal data mining: A survey
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big
spatial and spatiotemporal data. They are used in various application domains such as …
spatial and spatiotemporal data. They are used in various application domains such as …
Towards event prediction in temporal graphs
This paper proposes a class of temporal association rules, denoted by TACOs, for event
prediction. As opposed to previous graph rules, TACOs monitor updates to graphs, and can …
prediction. As opposed to previous graph rules, TACOs monitor updates to graphs, and can …
Prediction of Traffic Incident Clearance Duration Using Neural Network for Multimodal Data Distribution
Traffic incidents adversely affect the safety and mobility of our transportation network. As
such, accurate prediction of incident duration is critical in developing strategies and …
such, accurate prediction of incident duration is critical in developing strategies and …
Prediction of duration of traffic incidents by hybrid deep learning based on multi-source incomplete data
Q Shang, T Xie, Y Yu - … journal of environmental research and public …, 2022 - mdpi.com
Traffic accidents causing nonrecurrent congestion and road traffic injuries seriously affect
public safety. It is helpful for traffic operation and management to predict the duration of …
public safety. It is helpful for traffic operation and management to predict the duration of …
[PDF][PDF] Predicting incident duration based on machine learning methods
ZA Mohammed, MN Abdullah, IH Al Hussaini - Iraqi J. Comput. Commun …, 2021 - iasj.net
Traffic incidents dont only cause various levels of traffic congestion but often contribute to
traffic accidents and secondary accidents, resulting in substantial loss of life, economy, and …
traffic accidents and secondary accidents, resulting in substantial loss of life, economy, and …
A Review of Incident Prediction, Resource Allocation, and Dispatch Models for Emergency Management
In the last fifty years, researchers have developed statistical, data-driven, analytical, and
algorithmic approaches for designing and improving emergency response management …
algorithmic approaches for designing and improving emergency response management …
Anchor-Enhanced Geographical Entity Representation Learning
R Chen, J Lei, H Yao, T Li, S Li - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
Geographical entity representation learning (GERL) aims to embed geographical entities
into a low-dimensional vector space, which provides a generalized approach for utilizing …
into a low-dimensional vector space, which provides a generalized approach for utilizing …