Dynamic graph augmentation is used to improve the performance of dynamic GNNs. Most methods assume temporal locality, meaning that recent edges are more influential than earlier edges. However, for ...

The evaluation function that is based on the adjacency-constraint matrix calculates the fitness values to select the most efficient path. With only two constraints, the performance simulation results ...