Integration of the Kohonen's self-organising map and k-means algorithm for the segmentation of the AE data collected during tensile tests on cross-ply composites

By N. Godin, S. Huguet, R. Gaertner. 2005

231 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Mechanical Engineering, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/64f425f7e1fb6a2d74f6db4798e3a15bf10596b8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. P. Duchene
2. A. Ayadi
3. P. Krawczak
4. S. Chaki

In Mechanical Engineering

1. P. Duchene
2. A. Ayadi
3. P. Krawczak
4. S. Chaki

In Mechanics of Materials

1. P. Duchene
2. A. Ayadi
3. P. Krawczak
4. S. Chaki

Citations in the corpus

• A review of non-destructive techniques used for mechanical damage assessment in polymer composites (2018, methodology): “Other supervised (neural networks [32, 33]) or unsupervised (k-means [34], pattern recognition [29],.”
• Damage characterization of laminated composites using acoustic emission: A review (2020, unknown): “[117] Glass/epoxy Tensile 40–80 50–80 70–100 70–100 70–100”