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arXiv · 2305.09425

When is an SHM problem a Multi-Task-Learning problem?

Sarah Bee·Lawrence Bull·Nikolas Dervilis·Keith Worden
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Abstract

Multi-task neural networks learn tasks simultaneously to improve individual task performance. There are three mechanisms of multi-task learning (MTL) which are explored here for the context of structural health monitoring (SHM): (i) the natural occurrence of multiple tasks; (ii) using outputs as inputs (both linked to the recent research in population-based SHM (PBSHM)); and, (iii) additional loss functions to provide different insights. Each of these problem settings for MTL is detailed and an example is given.

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Sarah Bee, Lawrence Bull, Nikolas Dervilis, Keith Worden. 2023-05-16. When is an SHM problem a Multi-Task-Learning problem?. https://arxiv.org/abs/2305.09425

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