Improved method of χ2 - clusterization and its application to the analysis of emergency in automobile transport.
Abstract
There is a large variety of methods for data clustering, but all of them have numerous defects. On the one hand, it is the ambiguity of splitting the data array into groups, and on the other the impossibility to assess the degree of homogeneity of objects belonging to the same cluster. The purpose of thіs work is to develop the method for cluster analysis of multidimensional data of a different nature, which will ensure unambiguity of splitting a set of independent samples into clusters that do not intersect, so that the probability of false clustering does not exceed a certain predetermined level. The clustering method is based on the use of the χ2 consistency criterion.
Besides, the problem of accidents on road transport is quite acute in the domestic realities, since the level of accidents with victims significantly exceeds the average European. At that, the clustering of the regions of Ukraine according to the types of road accidents with the victims, their causes and culprits will help to understand the general regional factors affecting the accident rate, to identify and implement the best practices for its prevention. That is why the application of the proposed method to the analysis of accidents on road transport in Ukraine is quite relevant. The developed method is implemented programmatically and applied to a comparative analysis of the accident rate in road transport in the regions of Ukraine.
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