PEGNet: Integrating Peridynamics and Emergent Features into a Spatio-Temporal Graph Neural Network for Land Subsidence Modeling
- DOI
- 10.20944/preprints202607.2391.v1
- Published
- 2026-07-31
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- Not recorded
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.20944/preprints202607.2391.v1,
title = {PEGNet: Integrating Peridynamics and Emergent Features into a Spatio-Temporal Graph Neural Network for Land Subsidence Modeling},
author = {Siyuan Cheng and Xiaojuan Li and Roberto Tomás and Mi Chen and Lin Wang and Kan Wang},
year = {2026},
doi = {10.20944/preprints202607.2391.v1},
url = {https://doi.org/10.20944/preprints202607.2391.v1}
}RIS
TY - JOUR TI - PEGNet: Integrating Peridynamics and Emergent Features into a Spatio-Temporal Graph Neural Network for Land Subsidence Modeling AU - Siyuan Cheng AU - Xiaojuan Li AU - Roberto Tomás AU - Mi Chen AU - Lin Wang AU - Kan Wang PY - 2026 DO - 10.20944/preprints202607.2391.v1 UR - https://doi.org/10.20944/preprints202607.2391.v1 ER -
APA
Cheng, S., Li, X., Tomás, R., Chen, M., Wang, L., & Wang, K. (2026). PEGNet: Integrating Peridynamics and Emergent Features into a Spatio-Temporal Graph Neural Network for Land Subsidence Modeling. https://doi.org/10.20944/preprints202607.2391.v1
Source records
- crossref · retrieved 2026-09-25T06:12:23.137Z