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Titlebook: Data Science in Engineering, Volume 9; Proceedings of the 3 Ramin Madarshahian,Francois Hemez Conference proceedings 2022 The Society for E

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樓主: Coagulant
11#
發(fā)表于 2025-3-23 10:17:33 | 只看該作者
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發(fā)表于 2025-3-23 14:12:13 | 只看該作者
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發(fā)表于 2025-3-23 19:56:27 | 只看該作者
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發(fā)表于 2025-3-24 00:21:24 | 只看該作者
Vijayaraj Nagarajan,Mohamed O. Elasrit make it difficult to discern damage from environmental and operational (E&O) variability. Therefore, an improved process for identifying features that are sensitive to damage while insensitive to E&O effects is needed. In this study a SHM approach that utilizes causality metrics is proposed. The a
15#
發(fā)表于 2025-3-24 05:25:32 | 只看該作者
Sk Mohiuddin,Samir Malakar,Ram Sarkary resources to prepare a large volume of the ground truth of a dataset labeled at the pixel level. Hybrid crack segmentation (Kang et al., Autom Constr 118:103291, 2020) is based on the integration of a faster region-based convolutional neural network (faster R-CNN) as the deep learning-based object
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發(fā)表于 2025-3-24 10:11:57 | 只看該作者
https://doi.org/10.1007/978-3-030-75529-4d dynamics technology for structural health monitoring is being explored in order to optimize cost and improve performance. However, current imagers capture both the dynamic and static portions of a scene when only the dynamic portion is needed. The capture of both static and dynamic portions of a s
17#
發(fā)表于 2025-3-24 14:35:09 | 只看該作者
Sk Mohiuddin,Samir Malakar,Ram Sarkarat are not captured by the mathematical model assumed. These models are often reduced order models (ROM) that have simplified physics or have been obtained through data-driven techniques, such as trained neural networks. In this paper, we evaluate two data assimilation techniques to perform paramete
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發(fā)表于 2025-3-24 16:51:47 | 只看該作者
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發(fā)表于 2025-3-24 21:19:27 | 只看該作者
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