Deep neural networks for spatial-temporal cyber-physical systems: A survey
Cyber-physical systems (CPS) refer to systems that integrate communication, control, and
computational elements into physical processes to facilitate the control of physical systems …
computational elements into physical processes to facilitate the control of physical systems …
Temporal-spatial quantum graph convolutional neural network based on Schrödinger approach for traffic congestion prediction
Z Qu, X Liu, M Zheng - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Traffic congestion prediction (TCP) plays a vital role in intelligent transportation systems due
to its importance of traffic management. Methods for TCP have emerged greatly with the …
to its importance of traffic management. Methods for TCP have emerged greatly with the …
IoT-based traffic prediction and traffic signal control system for smart city
Because of the population increasing so high, and traffic density remaining the same, traffic
prediction has become a great challenge today. Creating a higher degree of communication …
prediction has become a great challenge today. Creating a higher degree of communication …
Meta graph transformer: A novel framework for spatial–temporal traffic prediction
Accurate traffic prediction is critical for enhancing the performance of intelligent
transportation systems. The key challenge to this task is how to properly model the complex …
transportation systems. The key challenge to this task is how to properly model the complex …
A novel framework to avoid traffic congestion and air pollution for sustainable development of smart cities
Traffic management is crucial for the sustainable development of smart cities. There has
been a continuous emphasis from the research community to predict air quality and manage …
been a continuous emphasis from the research community to predict air quality and manage …
Integrating the traffic science with representation learning for city-wide network congestion prediction
Recent studies on traffic congestion prediction have paved a promising path towards the
reduction of potential economic and environmental loss. However, at the city-wide scale …
reduction of potential economic and environmental loss. However, at the city-wide scale …
How weather impacts the citizens' activity patterns in southern China? Enlightenment from large-scale mobile phone signaling data of Guangzhou
In the realm of smart cities, understanding citizens' activity patterns is essential for effective
urban planning and development. Weather condition plays a crucial role in shaping citizen's …
urban planning and development. Weather condition plays a crucial role in shaping citizen's …
PFNet: Large-Scale Traffic Forecasting With Progressive Spatio-Temporal Fusion
C Wang, K Zuo, S Zhang, H Lei, P Hu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Traffic flow forecasting on a large-scale sensor network is of great practical significance for
policy decision-making, urban management, and transport planning. Recently, several …
policy decision-making, urban management, and transport planning. Recently, several …
Traffic congestion forecasting using multilayered deep neural network
This study proposes a multilayered deep neural network (MLDNN) and a congestion index
(CI) based on traffic density factor to forecast traffic congestion directly. Data were collected …
(CI) based on traffic density factor to forecast traffic congestion directly. Data were collected …
STTF: An efficient transformer model for traffic congestion prediction
With the rapid development of economy, the sharp increase in the number of urban cars and
the backwardness of urban road construction lead to serious traffic congestion of urban …
the backwardness of urban road construction lead to serious traffic congestion of urban …