Code is a collection of transfer learning algorithms that have been generated or applied in engineering contexts, particularly for structural health monitoring applications.
Code mainly to reproduce paper results (as close as possible given data-availability). Scripts for papers can be found in the demo folder.
To setup the files in MATLAB run setup.m to add folders to path.
These are the transfer learning models which can be found in the models folder.
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Homogeneous transfer learning
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Heterogeneous transfer learning
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On the application of domain adaptation for structural health monitoring
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Foundations of population-based SHM Part III: Heterogeneous populations - Mapping and Transfer
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Machine learning at the inferface of structural health monitoring and non-destructive evaluation [Open Access]
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Overcoming the problem of repair in structural health monitoring: Metric-informed transfer learning
- Demonstration of M-JDA on repair scenarios involving a Gnat aircraft
- Demo script is mjda_demo_gnat.m and is accompanied by a readme.
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On the application of kernelised Bayesian transfer learning to population-based structural health monitoring [Open Access]
- Application of KBTL to structural health monitoring applications
- Demo scripts are kbtl_demo_binary.m and kbtl_demo_multiclass.m and are accompanied by a readme.