Demand prediction for a public bike sharing program based on spatio-temporal graph convolutional networks.
Guangnian XiaoRuinan WangChunqin ZhangAnning NiPublished in: Multim. Tools Appl. (2021)
Keyphrases
- spatio temporal
- prediction accuracy
- average degree
- social networks
- random walk
- directed graph
- spatial and temporal
- graph structure
- neural network ensemble
- prediction model
- graph structures
- deep learning
- complex networks
- image sequences
- dynamic networks
- graph theory
- edge weights
- graph model
- fully connected
- small world
- social graphs
- graph representation
- prediction error
- moving objects
- graph mining
- graph layout
- connected components
- spatio temporal data
- information sharing
- space time
- overlapping communities
- community discovery
- graph mining algorithms
- directed edges
- semi supervised
- betweenness centrality
- citation networks
- spatio temporal databases
- knowledge sharing
- network structure
- link prediction
- graphical representation
- directed acyclic graph
- graph partitioning