graph neural networks

A QCGNN-Based Predictive Framework for a Common Sliding Mode Control for Enhanced Fault-Tolerant Performance of a Four-Wheel Independently Driven Electric Vehicle

The increasing popularity of electric vehicles is inevitable due to their lower dependence on conventional fuel and reduced air pollution. Among various drivetrain architectures, four-wheel independently driven electric vehicles (4WID-EVs) have gained significant attention owing to their superior load-carrying and dyna...

Datasets and Implementation Code for Resilient Real-Time Metro Rerouting Using Adaptive Bidirectional Heuristics and Graph Neural Networks

This repository contains the dataset, source codes, trained graph models, and experimental outputs used in the research article entitled: "Resilient Real-Time Metro Rerouting with Adaptive Bidirectional Heuristics and Graph Neural Network-Based Edge Prediction" The provided materials support the implementation and eval...

Joint optimization of spare part logistic operations and condition-based replacement policies in a system of geographically distributed multi-component assets

The Plasma Diagnostic Suite and Real-Time State Estimation for a Compact Spherical-Tokamak Breeder: Magnetics, Thomson, Interferometry, and Bolometry Fused by a Graph-Neural-Network Reconstructor

An autonomous controller can act only on the state it can see, and in a compact spherical tokamak the state must be produced faster than the plant evolves, from a diagnostic set that survives a 14 neutron field and keeps working when individual channels drop out. We formalise the Hyperion breeder diagnostic suite — mag...

The Plasma Diagnostic Suite and Real-Time State Estimation for a Compact Spherical-Tokamak Breeder: Magnetics, Thomson, Interferometry, and Bolometry Fused by a Graph-Neural-Network Reconstructor

An autonomous controller can act only on the state it can see, and in a compact spherical tokamak the state must be produced faster than the plant evolves, from a diagnostic set that survives a 14 neutron field and keeps working when individual channels drop out. We formalise the Hyperion breeder diagnostic suite — mag...

RatKpContext Benchmark (RKpC Benchmark): Aggregate Evaluation Outputs and Reproducibility Metadata for Tissue-Context-Aware Rat Kp Prediction

The RatKpContext Benchmark (RKpC Benchmark) is the data companion to the manuscript “Dissecting Tissue-Context Effects in Graph Neural Networks for Rat Kp Prediction: Additive Shifts, Fusion Position, and Extrapolation.” It contains aggregate evaluation outputs for four graph neural network architectures under repeated...

Plasma Protein Binding Prediction under Scaffold Split: Tree Models, ChemBERTa, Graph Networks, and Late Fusion

From idea generation to testing, drug discovery is a lengthy and expensive process. Rather than chasing all of their molecule ideas, scientists prioritize certain molecules that are more likely to be successful, from synthesis to safety to therapeutic use. Machine learning and AI enable researchers to narrow their cand...

Physics-Informed Digital Twins for Real-Time Health Monitoring Performance Prediction and Remaining Useful Life Assessment of Gas Turbines Foundations and Structural Support Systems

Gas turbines and their foundations and structural support systems operate as dynamically coupled thermo-mechanical assets whose degradation is governed by interacting aerodynamic, thermal, rotational, vibration, fatigue, settlement, stiffness-loss, and load-transfer mechanisms. Conventional condition-monitoring and rem...

Student Performance and Prediction in Student Management Based on the Louvain Algorithm and a Hybrid Neural Network Model

The efficiency and accuracy of existing student performance prediction technologies are low. This study proposes a prediction model that combines the Louvain algorithm and a hybrid neural network model. The model aims to improve the accuracy and efficiency of student performance prediction. The model uses graph folding...

Chest disease detection using federated multi-scale graph capsule network with light spectrum and dual attention

NEXUS-GO: Network-Extended Unified Sequence Embeddings for Gene Ontology Function Annotation

Protein function annotation by propagating protein language model embeddings over protein-protein interaction networks, across the full range from parameter-free multi-hop diffusion to learned graph neural networks (GCN, GAT, GraphSAGE) and their fusion. This release is the archived snapshot of the code and derived res...

High-throughput computational screening and thermodynamics-informed machine learning for lithium-based ceramic materials for high-temperature CO2 capture.

capture. A reaction-level graph neural network with transfer learning was proposed that efficiently predicted the temperature dependence of the carbonation reaction.