An Efficient Gradient-Free Topology Optimization Method Based on Superellipse Curves and a Multilayer Perceptron Surrogate
- DOI
- 10.3390/mi17091074
- Published
- 2026-09-10
- Container
- Micromachines
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/mi17091074,
title = {An Efficient Gradient-Free Topology Optimization Method Based on Superellipse Curves and a Multilayer Perceptron Surrogate},
author = {Fengyi Jin and Yanli Liu},
year = {2026},
journal = {Micromachines},
doi = {10.3390/mi17091074},
url = {https://doi.org/10.3390/mi17091074}
}RIS
TY - JOUR TI - An Efficient Gradient-Free Topology Optimization Method Based on Superellipse Curves and a Multilayer Perceptron Surrogate AU - Fengyi Jin AU - Yanli Liu PY - 2026 JO - Micromachines DO - 10.3390/mi17091074 UR - https://doi.org/10.3390/mi17091074 ER -
APA
Jin, F., & Liu, Y. (2026). An Efficient Gradient-Free Topology Optimization Method Based on Superellipse Curves and a Multilayer Perceptron Surrogate. Micromachines. https://doi.org/10.3390/mi17091074
Source records
- crossref · retrieved 2026-09-27T01:56:36.560Z