Volume 7, no. 1Pages 16 - 23

Statistical Evaluation of Professional Suitability of Operators of Extreme Activities with Using the Physical Modelling

Y.T. Volodarskiy, , L.A. Koshevaya, E.V. Bulygina
Authors offer a method for assessment of professional suitability of operators of extreme activities based on a statistical three-level criterion. It allows to assess the suitability of the operator on three consecutive stages and thereby improve the accuracy of the correct selection. As a generalized parameter by which the suitability of the operator can be assessed without involving experts, a coefficient of energetic sustainability is used. It's calculated as the ratio of the areas under the curve of the spectral density of $alpha$-rhythm of the biological signal of operator in a calm and loaded conditions. To determine possible scattering of relative value, called coefficient of energetic sustainability, which can be caused by 'individual' features of operators, or by the influence of extreme loads, or by conditions and mode of operation, a physical modelling experiment has been carried out. The group of operators (winter expedition to the Antarctic station 'Akademik Vernadsky') who's having a positive (long and successful) experience in extreme conditions, have been engaged in this experiment. However, the group had some individual variances within the required qualifications. As a result the 'standard' norms of scattering, sorted by affective random variables, have been set with respect to which the assessment is carried out in the process of selection of operators. Taking into account limited volume of samples in selection of operators in order to improve the statistical reliability of the assessments and, consequently, to improve the reliability of decisions about the suitability of operators it's used a robust procedure, which is based on the absolute median deviation. The approach proposed by authors allows to automate the selection procedure of operators and thereby exclude possible subjective decisions of experts.
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Keywords
statistical model; criterion; professional selection; reliability; robust estimate.
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