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The state of the application of the techniques of cluster analysis does not include the work accidents. The applications more established for statistical data analysis include pattern recognition, image analy-sis and information retrieval. The aim of this study is to provide a quantitative assessment, based on techniques of statistical processing of historical data in order to highlight the causality between the accident and predictive recurring events. On the basis of information provided by the analysis, it is possible to propose preven-tive strategies targeted to reducing the number of accidents (mainly the fatal accidents). Based on the collection of fatal accidents in the Infor.MO database (INAIL), we proceeded to aggre-gate accident cases registered in order to provide cluster analysis, which with reference to generators of the danger fl ow mortal areas, could show typical accidents, namely preferential genesis that, proposing the causes of the same energy mortal fl ow, could explain a large number of events. In order to run the analysis, a methodological assumption that describes the phenomenon of acci-dents, like any algebraic entity, as the case represented in algebraic space, is requested. The n dimensions useful to describe the phenomenon are the n generators of the danger areas. Based
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Lombardi et al. (2013) studied this question.
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