Graph neural network for traffic forecasting: The research progress
Traffic forecasting has been regarded as the basis for many intelligent transportation system
(ITS) applications, including but not limited to trip planning, road traffic control, and vehicle …
(ITS) applications, including but not limited to trip planning, road traffic control, and vehicle …
A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions
Deep learning has seen significant growth recently and is now applied to a wide range of
conventional use cases, including graphs. Graph data provides relational information …
conventional use cases, including graphs. Graph data provides relational information …
A survey of graph neural network based recommendation in social networks
X Li, L Sun, M Ling, Y Peng - Neurocomputing, 2023 - Elsevier
With the widespread popularization of social network platforms, user-generated content and
other social network data are growing rapidly. It is difficult for social users to select interested …
other social network data are growing rapidly. It is difficult for social users to select interested …
[HTML][HTML] Deep learning-powered vessel traffic flow prediction with spatial-temporal attributes and similarity grou**
Perceiving the future trend of Vessel Traffic Flow (VTF) in advance has great application
values in the maritime industry. However, using such big data from the Automatic …
values in the maritime industry. However, using such big data from the Automatic …
Federated deep learning for smart city edge-based applications
The growing quantities of data allow for advanced analysis. A prime example of it are smart
city applications with forecasting urban traffic flow as a key application. However, data …
city applications with forecasting urban traffic flow as a key application. However, data …
Energy processes prediction by a convolutional radial basis function network
If an approach based on the gradient steepest descent is utilized to adapt the parameters of
a radial basis function network, then it requires dimensionality reduction of the input dataset …
a radial basis function network, then it requires dimensionality reduction of the input dataset …
A comprehensive survey on applications of AI technologies to failure analysis of industrial systems
Component reliability plays a pivotal role in industrial systems, which are evolving with
larger complexity and higher dimensionality of data. It is insufficient to ensure reliability and …
larger complexity and higher dimensionality of data. It is insufficient to ensure reliability and …
A Comprehensive Survey on Resource management in 6G network based on internet of things
The transition to 6th Generation (6G) cellular networks offers significant improvements over
5th Generation (5G), enhancing data transfer, reducing latency, and improving network …
5th Generation (5G), enhancing data transfer, reducing latency, and improving network …
Multi-graph fusion based graph convolutional networks for traffic prediction
Traffic prediction is significant for transportation management and travel route planning, and
it is challenging as the spatial dependencies are complex and temporal patterns are …
it is challenging as the spatial dependencies are complex and temporal patterns are …
Improved artificial rabbits optimization with ensemble learning-based traffic flow monitoring on intelligent transportation system
Traffic flow monitoring plays a crucial role in Intelligent Transportation Systems (ITS) by
dealing with real-time data on traffic situations and allowing effectual traffic management …
dealing with real-time data on traffic situations and allowing effectual traffic management …