Analysis of Seismic Elastic Steel Structures Using a New Hybrid Optimization Deep Learning Model

In response to the insufficient performance of traditional seismic elastic analysis models for steel structures, this study proposes a deep layered feature learning network model in a mixed optimization point set metric space by combining cross attention mechanism, graph neural network, and random s...

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Vydané v:	IEEE access Ročník 13; s. 1
Hlavní autori:	Li, Ping, Liu, Wanfeng, Yan, Tiecheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.01.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accuracy Adaptation models Analytical models Computational modeling Cross attention Deep learning Deformable models Deformation Elastic analysis Elasticity testing Feature extraction Graph neural networks Machine learning Matching Metric space Noise reduction Noise sensitivity Occlusion Optimization Peak values Point cloud compression PointNet Random sampling RANSAC Real time Seismic analysis Semantic segmentation Steel Steel pipes Steel structure Steel structures
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
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