Partial differential grey model based on control matrix and its application in short-term traffic flow prediction
H Duan, G Wang - Applied Mathematical Modelling, 2023 - Elsevier
Short-term traffic flow analysis is the core part of the intelligent transportation system, and
also the critical basis for traffic management and control system to guide traffic flow. Real …
also the critical basis for traffic management and control system to guide traffic flow. Real …
[HTML][HTML] Quantitative analysis of the impact of COVID-19 on ship visiting behaviors to ports-A framework and a case study
Abstract Corona Virus Disease 2019 (COVID-19) outbreak leads to a significant downturn in
the global economy and supply chain. In the maritime sector, trade volume slumped by 3.8 …
the global economy and supply chain. In the maritime sector, trade volume slumped by 3.8 …
Urban regional function guided traffic flow prediction
The prediction of traffic flow is a challenging yet crucial problem in spatial-temporal analysis,
which has recently gained increasing interest. In addition to spatial-temporal correlations …
which has recently gained increasing interest. In addition to spatial-temporal correlations …
ST-DAGCN: A spatiotemporal dual adaptive graph convolutional network model for traffic prediction
Accurately predicting traffic flow characteristics is crucial for effective urban transportation
management. Emergence of artificial intelligence has led to the surge of deep learning …
management. Emergence of artificial intelligence has led to the surge of deep learning …
DyGCN-LSTM: A dynamic GCN-LSTM based encoder-decoder framework for multistep traffic prediction
Intelligent transportation systems (ITS) are gaining attraction in large cities for better traffic
management. Traffic forecasting is an important part of ITS, but a difficult one due to the …
management. Traffic forecasting is an important part of ITS, but a difficult one due to the …
Spatio-temporal fusion and contrastive learning for urban flow prediction
Urban flow prediction is critical for urban planning, management, and safety. However,
owing to the inherent instability of urban flows, prediction accuracy requires the fusion of …
owing to the inherent instability of urban flows, prediction accuracy requires the fusion of …
Multi-stage deep residual collaboration learning framework for complex spatial–temporal traffic data imputation
Performing accurate and efficient traffic data repair has become an essential task before
proceeding with other applications of intelligent transportation systems. However, existing …
proceeding with other applications of intelligent transportation systems. However, existing …
Confined attention mechanism enabled Recurrent Neural Network framework to improve traffic flow prediction
Abstract Traffic Flow Prediction (TFP) is one of the most challenging issues and hard-core
requirement for an Intelligent Transportation System (ITS) around the globe. The outcomes …
requirement for an Intelligent Transportation System (ITS) around the globe. The outcomes …
A graph attention fusion network for event-driven traffic speed prediction
Accurate road traffic speed prediction has a critical role in intelligent transportation systems
and smart cities. This task is very challenging because of the complexity of road network …
and smart cities. This task is very challenging because of the complexity of road network …
Improved traffic sign detection algorithm based on faster R-CNN
X Gao, L Chen, K Wang, X **ong, H Wang, Y Li - Applied Sciences, 2022 - mdpi.com
The traffic sign detection algorithm based on Faster Region-Based Convolutional Neural
Network (R-CNN) has been applied to various intelligent-vehicles driving scenarios …
Network (R-CNN) has been applied to various intelligent-vehicles driving scenarios …