Graph neural network-based surrogate modelling for real-time hydraulic prediction of urban drainage networks.
Zhiyu ZhangChenkaixiang LuWenchong TianZhenliang LiaoZhiguo YuanPublished in: CoRR (2024)
Keyphrases
- real time
- prediction accuracy
- control system
- neural network
- edge weights
- average degree
- low cost
- highly connected
- neural network ensemble
- protein function prediction
- directed graph
- protein interaction networks
- fully connected
- graph structure
- prediction model
- graph matching
- network structure
- random walk
- social networks
- graph theory
- prediction error
- spanning tree
- graph representation
- graph theoretic
- vision system
- dynamic networks
- transportation networks
- degree distribution
- clustering coefficient
- community discovery
- transport network
- graph structures
- path length
- small world
- power law
- graph mining
- weighted graph
- complex networks
- structured data
- shortest path
- high speed