Sychophysiological Parameters of Students Before and After Translatitude Travels

The use of instrumental and non-invasive methods using a computer provides an opportunity to assess the state of the complex of psychophysiological functions and identify the most significant parameters in various environmental conditions. The aim of the study was a comparative analysis of two approaches: traditional statistical methods and artificial neural networks (ANN) based on a supercomputer in the study of the influence of translatitude relocation on psychophysiological functions. Methods: In total, 146 students, permamnent residents of Surgut from the 1st through the 7th grades were examined before and after travels from the north to the south of the Russian Federation and back. The state of the psychophysiological functions of students was recorded by using a patented software. The ANN was used to establish the differences in the state of psychophysiological parameters between the groups of boys and girls before from the north to the south (Tuapse) and after arriving back to Surgut. After multiple repetitions (p→∞) of this procedure, for each Pi after the j-th repetition, we obtained the total number of chaotic generation of values of weight coefficient wif processed in the framework of traditional stochastic (the distribution functions f(x) were determined). Moreover, these analyses were repeated in the sets р1 = 50, р2 = 100, р3 = 1 000. Results: We found that the dynamics of parameters of psychophysiological functions of characterizing the concentration and memory states, increased sharply and significantly in changes of the variation coefficients (Δwi) with a large number of neural network iterations in the binary classification mode. Conclusion: ANN in the mode of multiple iterations (P. ≥ 1 000) can provide a solution to the problem of system synthesis - identification of the most significant diagnostic features in the work of psychophysiological functions before and after short term north-south travels

Algorithm · Arithmetic · Artificial neural network · Binary number · Chaotic · Relocation · Statistics · Computer Science · Fusion and Plasma Physics Studies · Human Health and Disease · Mathematics · Psychology · Technology and Human Factors in Education and Health · Artificial Intelligence

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