Deep deterministic policy gradient and graph convolutional network for bracing direction optimization of grid shells
In this paper, we propose a method for bracing direction optimization of grid shells using a Deep Deterministic Policy Gradient (DDPG) and Graph Convolutional Network (GCN). DDPG allows simultaneous adjustment of variables during the optimization process, and GCN allows the DDPG agent to receive dat...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-08-01
|
| Series: | Frontiers in Built Environment |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbuil.2022.899072/full |