Highlights •An innovative GNN-based method for the shear wall layout design that seamlessly integrates design conditions.•The proposed method outperforms others that overlook the importance of embedding design conditions.•The proposed method is versatile and adaptive to arbitrary combinations of design conditions. DOI: 10.1016/j.aei.2023.102190 Language: English Subjects: Graph neural network; Design conditions; Shear wall structure; Intelligent shear wall layout design; Deep learning; plink: https://research.ebsco.com/linkprocessor/plink?id=885d3c7f-ff59-33a5-ad8ae2b991f9c33c
| Authors | Zhao, P.; Liao, W.; Xue, Y.; Li, L.; Lu, X. |
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| Year | 2023 |
| Venue | Advanced Engineering Informatics 58, 102190 |
| DOI | 10.1016/j.aei.2023.102190 |
| Source Database | Backtracking |
| Bridge-to-GNN | Category A |
| GNN Architecture | GNN (heuristic — verify) |
| Graph Encoding | Structural Connectivity Graph (inferred from title) |
| AEC Task | Not yet extracted from PDF |
| Cohort | Consolidation (2023) |
| Quality Assessment | 1/6 · rigor: Low · Baseline: ✓ (heuristic — verify) |
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| GNN architectures detected | GNN (general) |
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| Quality (heuristic, 6-flag) | 1/6 · rigor: Low Code/Data: —Benchmark: —Baseline: ✓CV/Split: —Ablation: —Reproducible: — |
| Seed of .bib export → verified neighbours | This paper was queried as a Connected Papers seed (41 entries scanned). In-corpus neighbours verified by the bibliometric ranking: [40] 2022 · Buruzs · IFC BIM Model Enrichment with Space Function Information… [41] 2022 · Lygerakis · Knowledge Graphs' Ontologies and Applications for Energy… |
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Part of the GML/GNN in AEC Systematic Review (PRISMA 2020) — 112 papers, 2020–2026