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GCN-DRL Model for Water Network Resilience by 阙绮东 is a document available to read on EtoBox.

What is GCN-DRL Model for Water Network Resilience about?

This article presents a graph convolutional neural network-deep reinforcement learning (GCN-DRL) model to determine optimal repair sequences for water distribution networks after earthquakes to improve resilience. The GCN-DRL model encodes network topology and performance to generate reward values for repair actions. It is tested on an example network under damage scenarios and compared to other methods, showing it achieves higher resilience and faster recovery.

Author

阙绮东

Language

EN