Physics-Guided Neural Surrogate Model with Particle Swarm-Based Multi-Objective Optimization for Quasi-Coaxial TSV Interconnect Design
- DOI
- 10.3390/mi16101134
- Published
- 2025-09-30
- Container
- Micromachines
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/mi16101134,
title = {Physics-Guided Neural Surrogate Model with Particle Swarm-Based Multi-Objective Optimization for Quasi-Coaxial TSV Interconnect Design},
author = {Zheng Liu and Guangbao Shan and Zeyu Chen and Yintang Yang},
year = {2025},
journal = {Micromachines},
doi = {10.3390/mi16101134},
url = {https://doi.org/10.3390/mi16101134}
}RIS
TY - JOUR TI - Physics-Guided Neural Surrogate Model with Particle Swarm-Based Multi-Objective Optimization for Quasi-Coaxial TSV Interconnect Design AU - Zheng Liu AU - Guangbao Shan AU - Zeyu Chen AU - Yintang Yang PY - 2025 JO - Micromachines DO - 10.3390/mi16101134 UR - https://doi.org/10.3390/mi16101134 ER -
APA
Liu, Z., Shan, G., Chen, Z., & Yang, Y. (2025). Physics-Guided Neural Surrogate Model with Particle Swarm-Based Multi-Objective Optimization for Quasi-Coaxial TSV Interconnect Design. Micromachines. https://doi.org/10.3390/mi16101134
Source records
- crossref · retrieved 2026-11-10T10:49:10.861Z