Nature

Graph neural network-based cell switching for energy optimization in ultra-dense heterogeneous networks

The development of ultra-dense heterogeneous networks (HetNets) will cause a significant rise in energy consumption with large-scale base station (BS) deployments, requiring cellular networks to be ...
Nature

Federated two-edge graph attention network with weighted global aggregation for electricity consumption demand forecasting

Accurate electricity demand forecasting is crucial for the stable operation of smart grids, as it enables proactive resource allocation and prevents grid failures caused by demand–supply mismatches.
EurekAlert!

GAME-Net: a graph neural network for fast evaluation of the adsorption energy in heterogeneous catalysis

Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking ...
dbta

Recognizing the Power of Graph Databases and Knowledge Graphs

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...