Archivio Istituzionale della RicercaA data analysis method for occupational accident databases. The approach is based on the joint use of Kohonen’s SOM and k-means clustering. The novelty aspect is the visualization capability offered to the analyst. The method was applied to accidents occurred in the Italian wood processing industry.
Self-Organizing Map and clustering algorithms for the analysis of occupational accident databases / Palamara, Federica; Piglione, Federico; Piccinini, Norberto. - In: SAFETY SCIENCE. - ISSN 0925-7535. - STAMPA. - 49:8-9(2011), pp. 1215-1230. [10.1016/j.ssci.2011.04.003]
Self-Organizing Map and clustering algorithms for the analysis of occupational accident databases
PALAMARA, FEDERICA;PIGLIONE, Federico;PICCININI, Norberto
2011
Abstract
A data analysis method for occupational accident databases. The approach is based on the joint use of Kohonen’s SOM and k-means clustering. The novelty aspect is the visualization capability offered to the analyst. The method was applied to accidents occurred in the Italian wood processing industry.
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https://hdl.handle.net/11583/2426396
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