Fig. 11From: A deep reinforcement learning model for resilient road network recovery under earthquake or flooding hazardsComparison of system recovery under different new damage scenarios based on repairing sequence determined by different decision methods (i.e., pre-trained GCN-DRL model, genetic algorithm, betweenness centrality)Back to article page