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Applications of Graph Neural Networks in Civil Infrastructures: A Review on Transportation, Power, Water, and Structural Systems
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Graph Neural Network and Imaging Based Vehicle Classification for Traffic Monitoring System
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STGNet: Short‐term residential load forecasting with spatial–temporal gated fusion network
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Graph Neural Network enhanced Finite Element modelling
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Structured Sequence Modeling with Graph Convolutional Recurrent Networks
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Bayesian Graph Neural Networks for Strain-Based Crack Localization
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Structural Form-Finding Enhanced by Graph Neural Networks
inferredcites →https://doi.org/10.1007/978-3-031-30047-9_3openalex-snapshot
Spatial Graph Convolution Neural Networks for Water Distribution Systems
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Topological Graph Convolutional Networks Solutions for Power Distribution Grid Planning
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Traffic Flow Prediction Based on Multi-type Characteristic Hybrid Graph Neural Network
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DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks
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Multi-modal Recurrent Graph Neural Networks for Spatiotemporal Forecasting
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GraphNILM: A Graph Neural Network for Energy Disaggregation
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Graph-Based Dependency-Aware Non-Intrusive Load Monitoring
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Gated Fusion Adaptive Graph Neural Network for Urban Road Traffic Flow Prediction
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Graph Convolutional Neural Network for Pressure Prediction in Water Distribution Network Sites
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Evaluating the Impact of Digital Elevation Models on Urban Flood Modeling: A Comprehensive Analysis of Flood Inundation, Hazard Mapping, and Damage Estimation
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Traffic Flow Forecasting Based on Transformer with Diffusion Graph Attention Network
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Graph attention neural network for water network partitioning
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Predicting Construction Accident Outcomes Using Graph Convolutional and Dual-Edge Safety Networks
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A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation
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Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution
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Multi-task Framework for Vibration-Based Structural Damage Detection of Spatial Truss Structure Using Graph Learning
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Hybrid LSTM-Graph Convolutional Neural Network with Wavelet Transform and Correlation Analysis for Electrical Demand Forecasting
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Attention based spatio-temporal graph convolutional network with focal loss for crash risk evaluation on urban road traffic network based on multi-source risks
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Graph neural networks: A review of methods and applications
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Explainable Spatio-Temporal Graph Neural Networks for multi-site photovoltaic energy production
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Applicability analysis of transformer to wind speed forecasting by a novel deep learning framework with multiple atmospheric variables
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Physics-informed graphical neural network for power system state estimation
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A physics-informed graph learning approach for citywide electric vehicle charging demand prediction and pricing
inferredcites →https://doi.org/10.1016/j.apenergy.2024.123194openalex-snapshot
GGNet: A novel graph structure for power forecasting in renewable power plants considering temporal lead-lag correlations
inferredcites →https://doi.org/10.1016/j.apenergy.2024.123252openalex-snapshot
ST-AGNet: Dynamic power system state prediction with spatial–temporal attention graph-based network
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Day-ahead electricity price prediction in multi-price zones based on multi-view fusion spatio-temporal graph neural network
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Data-augmentation acceleration framework by graph neural network for near-optimal unit commitment
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TSO-GCN: A Graph Convolutional Network approach for real-time and generalizable truss structural optimization
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Data-unbalanced traffic accident prediction via adaptive graph and self-supervised learning
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Comparing modern and traditional modeling methods for predicting soil moisture in IoT-based irrigation systems
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Automated structural design optimization of steel reinforcement using graph neural network and exploratory genetic algorithms
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Graph neural networks for construction applications
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Multi-step trend aware graph neural network for traffic flow forecasting
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Spatio-temporal heterogeneous graph using multivariate earth observation time series: Application for drought forecasting
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Koopman theory meets graph convolutional network: Learning the complex dynamics of non-stationary highway traffic flow for spatiotemporal prediction
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Advancing storm surge forecasting from scarce observation data: A causal-inference based Spatio-Temporal Graph Neural Network approach
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Graph Neural Network-based surrogate model for granular flows
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Machine learning prediction of structural dynamic responses using graph neural networks
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StructGNN: An efficient graph neural network framework for static structural analysis
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Vertex-based graph neural network classification model considering structural topological features for structural optimization
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Digital twin assisted decision support system for quality regulation and leak localization task in large-scale water distribution networks
inferredcites →https://doi.org/10.1016/j.displa.2023.102513openalex-snapshot
RL-GCN: Traffic flow prediction based on graph convolution and reinforcement learning for smart cities
inferredcites →https://doi.org/10.1016/j.egyai.2023.100262openalex-snapshot
Power flow forecasts at transmission grid nodes using Graph Neural Networks
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Electricity demand forecasting at distribution and household levels using explainable causal graph neural network
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Boosting efficiency in state estimation of power systems by leveraging attention mechanism
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Graph reinforcement learning for power grids: A comprehensive survey
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TransformGraph: A novel short-term electricity net load forecasting model
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Forced oscillation location based on temporal graph convolutional network
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Multi-task transient stability assessment of power system based on graph neural network with interpretable attribution analysis
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ACGL-TR: A deep learning model for spatio-temporal short-term irradiance forecast
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The data-based adaptive graph learning network for analysis and prediction of offshore wind speed
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Spatiotemporal analysis of bidimensional wind speed forecasting: Development and thorough assessment of LSTM and ensemble graph neural networks on the Dutch database
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A D-stacking dual-fusion, spatio-temporal graph deep neural network based on a multi-integrated overlay for short-term wind-farm cluster power multi-step prediction
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A spatio-temporal forecasting model using optimally weighted graph convolutional network and gated recurrent unit for wind speed of different sites distributed in an offshore wind farm
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A novel spatial–temporal generative autoencoder for wind speed uncertainty forecasting
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Sub-region division based short-term regional distributed PV power forecasting method considering spatio-temporal correlations
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Ultra-short-term wind farm cluster power prediction based on FC-GCN and trend-aware switching mechanism
inferredcites →https://doi.org/10.1016/j.energy.2024.130404openalex-snapshot
GAOformer: An adaptive spatiotemporal feature fusion transformer utilizing GAT and optimizable graph matrixes for offshore wind speed prediction
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An ultra-short-term wind power prediction method based on spatial-temporal attention graph convolutional model
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A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information
inferredcites →https://doi.org/10.1016/j.energy.2024.130930openalex-snapshot
A novel dynamic spatio-temporal graph convolutional network for wind speed interval prediction
inferredcites →https://doi.org/10.1016/j.energy.2024.130931openalex-snapshot
A GCN-based adaptive generative adversarial network model for short-term wind speed scenario prediction
inferredcites →https://doi.org/10.1016/j.energy.2024.131131openalex-snapshot
A hybrid graph attention network based method for interval prediction of shipboard solar irradiation
inferredcites →https://doi.org/10.1016/j.energy.2024.131164openalex-snapshot
Spatial correlation learning based on graph neural network for medium-term wind power forecasting
inferredcites →https://doi.org/10.1016/j.energy.2024.132018openalex-snapshot
Multi-energy flow calculation in integrated energy system via topological graph attention convolutional network with transfer learning
inferredcites →https://doi.org/10.1016/j.energy.2024.132056openalex-snapshot
Self-supervised dynamic stochastic graph network for spatio-temporal wind speed forecasting
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Integrated dynamic multi-threshold pattern recognition with graph attention long short-term neural memory network for water distribution network losses prediction: An automated expert system
inferredcites →https://doi.org/10.1016/j.engappai.2024.108135openalex-snapshot
Residual attention enhanced Time-varying Multi-Factor Graph Convolutional Network for traffic flow prediction
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Intelligent identification of power grid parameters based on dynamic weighting
inferredcites →https://doi.org/10.1016/j.engappai.2024.109010openalex-snapshot
Multiscale information enhanced spatial-temporal graph convolutional network for multivariate traffic flow forecasting via magnifying perceptual scope
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Enhanced multi-scenario running safety assessment of railway bridges based on graph neural networks with self-evolutionary capability
inferredcites →https://doi.org/10.1016/j.epsr.2023.109873openalex-snapshot
Short-term load forecasting using spatial-temporal embedding graph neural network
inferredcites →https://doi.org/10.1016/j.epsr.2023.109965openalex-snapshot
Ultra-short-term prediction of regional photovoltaic power based on dynamic graph convolutional neural network
inferredcites →https://doi.org/10.1016/j.epsr.2024.110263openalex-snapshot
Graph Convolutional Networks based short-term load forecasting: Leveraging spatial information for improved accuracy
inferredcites →https://doi.org/10.1016/j.epsr.2024.110265openalex-snapshot
A short-term load forecasting method for integrated community energy system based on STGCN
inferredcites →https://doi.org/10.1016/j.epsr.2024.110427openalex-snapshot
Short-term load forecasting of regional integrated energy system based on spatio-temporal convolutional graph neural network
inferredcites →https://doi.org/10.1016/j.epsr.2024.110658openalex-snapshot
Topology-aware reinforcement learning for tertiary voltage control
inferredcites →https://doi.org/10.1016/j.epsr.2024.110738openalex-snapshot
Cascading blackout severity prediction with statistically-augmented graph neural networks
inferredcites →https://doi.org/10.1016/j.epsr.2024.110782openalex-snapshot
Initial estimate of AC optimal power flow with graph neural networks
inferredcites →https://doi.org/10.1016/j.epsr.2024.110795openalex-snapshot
Physics-informed heterogeneous graph neural networks for DC blocker placement
inferredcites →https://doi.org/10.1016/j.epsr.2024.110816openalex-snapshot
Distributed sequential optimal power flow under uncertainty in power distribution systems: A data-driven approach
inferredcites →https://doi.org/10.1016/j.epsr.2024.110817openalex-snapshot
Physics-informed Graph Neural Network for Dynamic Reconfiguration of power systems
inferredcites →https://doi.org/10.1016/j.epsr.2024.110864openalex-snapshot
Probabilistic power flow based on physics-guided graph neural networks
inferredcites →https://doi.org/10.1016/j.epsr.2024.111014openalex-snapshot
Multi-fidelity graph neural networks for efficient power flow analysis under high-dimensional demand and renewable generation uncertainty
inferredcites →https://doi.org/10.1016/j.eswa.2023.120010openalex-snapshot
Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity markets
inferredcites →https://doi.org/10.1016/j.eswa.2023.121070openalex-snapshot
Progressive decision-making framework for power system topology control
inferredcites →https://doi.org/10.1016/j.eswa.2023.121313openalex-snapshot
Multi-site solar irradiance forecasting based on adaptive spatiotemporal graph convolutional network
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Detection of false data injection attack in power grid based on spatial-temporal transformer network
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MSGCN-ISTL: A multi-scaled self-attention-enhanced graph convolutional network with improved STL decomposition for probabilistic load forecasting
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Deep graph gated recurrent unit network-based spatial–temporal multi-task learning for intelligent information fusion of multiple sites with application in short-term spatial–temporal probabilistic forecast of photovoltaic power
inferredcites →https://doi.org/10.1016/j.eswa.2024.124430openalex-snapshot
Adaptive graph neural network for traffic flow prediction considering time variation
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PI-STGnet: Physics-integrated spatiotemporal graph neural network with fundamental diagram learner for highway traffic flow prediction
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Dynamic multi-scale spatial–temporal graph convolutional network for traffic flow prediction
inferredcites →https://doi.org/10.1016/j.ifacol.2024.05.046openalex-snapshot
Sensor Placement in Water Distribution Networks using Graph Neural Networks
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Multi-agent graph reinforcement learning for decentralized Volt-VAR control in power distribution systems
inferredcites →https://doi.org/10.1016/j.ijepes.2023.109641openalex-snapshot
Physics-Informed Multi-Agent deep reinforcement learning enabled distributed voltage control for active distribution network using PV inverters
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Edge-graph convolution and multi-hop attention jointly driven small-signal stability assessment against topology changes
inferredcites →https://doi.org/10.1016/j.ijepes.2024.110074openalex-snapshot
Enhancing multivariate, multi-step residential load forecasting with spatiotemporal graph attention-enabled transformer
inferredcites →https://doi.org/10.1016/j.ijepes.2024.110112openalex-snapshot
PowerFlowNet: Power flow approximation using message passing Graph Neural Networks
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Stochastic dynamic power dispatch with high generalization and few-shot adaption via contextual meta graph reinforcement learning
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A topology-guided high-quality solution learning framework for security-constraint unit commitment based on graph convolutional network
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Forecasting day-ahead electricity prices with spatial dependence
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Traffic flow matrix-based graph neural network with attention mechanism for traffic flow prediction
inferredcites →https://doi.org/10.1016/j.inffus.2023.102196openalex-snapshot
Spatio-temporal fusion graph convolutional network for traffic flow forecasting
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PLU-MCN: Perturbation learning enhanced U-shaped multi-graph convolutional network for traffic flow prediction
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STGAFormer: Spatial–temporal Gated Attention Transformer based Graph Neural Network for traffic flow forecasting
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FedAGAT: Real-time traffic flow prediction based on federated community and adaptive graph attention network
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Interactive dynamic diffusion graph convolutional network for traffic flow prediction
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Structural damage detection framework based on graph convolutional network directly using vibration data
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Semi-supervised vibration-based structural health monitoring via deep graph learning and contrastive learning
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On the use of mechanics-informed models to structural engineering systems: Application of graph neural networks for structural analysis
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Adaptive GN block-based model for seismic response prediction of train-bridge coupled systems
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Fast prediction and control of air core in hydrocyclone by machine learning to stabilize operations
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Gated graph neural networks for identifying contamination sources in water distribution systems
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Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE)
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Simulation of spring discharge using graph neural networks at Niangziguan Springs, China
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Exploring a spatiotemporal hetero graph-based long short-term memory model for multi-step-ahead flood forecasting
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Urban flood vulnerability Knowledge-Graph based on remote sensing and textual bimodal data fusion
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A Comprehensive Review of Artificial Intelligence Techniques for Power Quality Improvement in Renewable Energy-Based Microgrids: Recent Trends, Challenges, and Future Directions
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