Application of self-organizing map to failure modes and effects analysis methodology
In this paper, a self-organizing map (SOM) neural network is used to visualize corrective actions of failure modes and effects analysis (FMEA). SOM is a popular unsupervised neural network model that aims to produce a low-dimensional map (typically a two-dimensional map) for visualizing high-dimensi...
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| 主要な著者: | , , |
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| フォーマット: | E-Article |
| 言語: | English |
| 出版事項: |
Elsevier
2017
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| 主題: | |
| オンライン･アクセス: | http://ir.unimas.my/id/eprint/15892/7/Application%20of%20self-organizing%20map%20to%20failure%20modes%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/15892/ http://www.sciencedirect.com/science/article/pii/S0925231217305702 |
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