WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting.
Theodoros TheodoropoulosAngelos-Christos MaroudisAntonios MakrisKonstantinos TserpesPublished in: CoRR (2024)
Keyphrases
- spatio temporal
- neural network
- recurrent neural networks
- weighted graph
- pattern recognition
- movement patterns
- random walk
- artificial neural networks
- directed acyclic graph
- graph structure
- graph theory
- spatio temporal data
- edge weights
- graph model
- traffic flow
- fuzzy logic
- network traffic
- spatial and temporal
- feed forward
- image sequences
- short term
- spectral graph
- structured data
- maximum weight
- graph theoretic
- genetic algorithm
- association graph
- financial forecasting
- chaotic time series
- bipartite graph
- multilayer perceptron
- directed graph
- computer vision
- traffic volume
- weight matrix
- moving objects
- logistics demand
- short term prediction
- exchange rate
- graph partitioning
- graph databases
- graph mining
- fault diagnosis
- support vector regression
- spatial data
- real time
- graph matching
- connected components