Abstract
In the technogenic sphere, and not only, there are socially resonant events that bring significant damage to the social sphere. An adequate prediction of such events is required to prevent and minimize damage from them. There are various methods for predicting accidents and disasters, determining the ultimate level of probability of occurrence or the absence of an event. However, forecasting, as a rule, is complicated by the small number of them. The general statistical aggregate of risk events is limited and does not allow us to apply the theory of probability. As a result, a new method of mathematical statistics has been developed, the application of which makes it possible to predict events with a certain probability on the basis of relatively small statistical data. It is proposed that a new approach to determine the probability of interesting events, with a limited general statistical sample, will allow to predict possible threats, with the greatest likelihood.
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Betskov, A., Makarov, V., Kilmashkina, T., Ovchinsky, A. (2019). On the Possibility of an Event Prediction with Limited Initial Statistical Data. In: Kravets, A. (eds) Big Data-driven World: Legislation Issues and Control Technologies. Studies in Systems, Decision and Control, vol 181. Springer, Cham. https://doi.org/10.1007/978-3-030-01358-5_4
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DOI: https://doi.org/10.1007/978-3-030-01358-5_4
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