Predicting the degree of rubber rupture damage using a GAN-enhanced Bayesian-optimized 1DCNN network
| Autor(en): |
Yi Zeng
(MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China)
Chubing Deng (MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China) Feng Xiong (MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China) Hong Liu (Chengdu Fourth Construction Engineering of CDCEG, Chengdu, China) Xiongfei Li (Chengdu Fourth Construction Engineering of CDCEG, Chengdu, China) Ye Liu
(MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China)
|
|---|---|
| Medium: | Fachartikel |
| Sprache(n): | Englisch |
| Veröffentlicht in: | Structural Health Monitoring |
| DOI: | 10.1177/14759217241279095 |
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Datenseite - Reference-ID
10806181 - Veröffentlicht am:
10.11.2024 - Geändert am:
10.11.2024
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