A review of traffic congestion prediction using artificial intelligence
M Akhtar, S Moridpour - Journal of Advanced Transportation, 2021 - Wiley Online Library
In recent years, traffic congestion prediction has led to a growing research area, especially
of machine learning of artificial intelligence (AI). With the introduction of big data by …
of machine learning of artificial intelligence (AI). With the introduction of big data by …
A comprehensive study of speed prediction in transportation system: From vehicle to traffic
In the intelligent transportation system (ITS), speed prediction plays a significant role in
supporting vehicle routing and traffic guidance. Recently, a considerable amount of research …
supporting vehicle routing and traffic guidance. Recently, a considerable amount of research …
Traffic graph convolutional recurrent neural network: A deep learning framework for network-scale traffic learning and forecasting
Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due
to the time-varying traffic patterns and the complicated spatial dependencies on road …
to the time-varying traffic patterns and the complicated spatial dependencies on road …
Multi-class multi-label ophthalmological disease detection using transfer learning based convolutional neural network
Fundus imaging is a retinal image modality for capturing anatomical structures and
abnormalities in the human eye. Fundus images are the primary tool for observation and …
abnormalities in the human eye. Fundus images are the primary tool for observation and …
Short-term prediction of lane-level traffic speeds: A fusion deep learning model
Accurate and robust short-term traffic prediction is an important part of advanced traveler
information systems. With the development of intelligent navigation and autonomous driving …
information systems. With the development of intelligent navigation and autonomous driving …
A ship movement classification based on Automatic Identification System (AIS) data using Convolutional Neural Network
X Chen, Y Liu, K Achuthan, X Zhang - Ocean Engineering, 2020 - Elsevier
With a wide use of AIS data in maritime transportation, there is an increasing demand to
develop algorithms to efficiently classify a ship's AIS data into different movements (static …
develop algorithms to efficiently classify a ship's AIS data into different movements (static …
A grey convolutional neural network model for traffic flow prediction under traffic accidents
Y Liu, C Wu, J Wen, X Xiao, Z Chen - Neurocomputing, 2022 - Elsevier
Accurate traffic flow prediction can effectively improve traffic efficiency and safety. This has
become a trending topic in intelligent transportation systems. However, the occurrence of …
become a trending topic in intelligent transportation systems. However, the occurrence of …
Traffic congestion propagation inference using dynamic Bayesian graph convolution network
Congestion, whether recurrent or non-recurrent, propagates through the road network. The
process of congestion propagation from a particular road to its neighbors can be regarded …
process of congestion propagation from a particular road to its neighbors can be regarded …
When intelligent transportation systems sensing meets edge computing: Vision and challenges
The widespread use of mobile devices and sensors has motivated data-driven applications
that can leverage the power of big data to benefit many aspects of our daily life, such as …
that can leverage the power of big data to benefit many aspects of our daily life, such as …
Renewable-based microgrids' energy management using smart deep learning techniques: Realistic digital twin case
Q Li, Z Cui, Y Cai, Y Su, B Wang - Solar Energy, 2023 - Elsevier
In this research study, a novel demand response program (DRP) has been proposed for
renewable-based microgrids (MGs) which takes into account the high penetration of tidal …
renewable-based microgrids (MGs) which takes into account the high penetration of tidal …