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Non-parametric model of learning for a system of diagnostics of psycho- physiological qualities
Poriadin Anton

graduate student, Department of Information and Computer Systems, Volga State University of Technology

424000, Russia, Marii El, g. Ioshkar-Ola, Ploshchad' Lenina, 3

lazy.ant10@gmail.com
Oparin Kirill

graduate student, Department of Information and Computer Systems, Volga State University of Technology

424000, Russia, Marii El oblast', g. Ioshkar-Ola, ul. Ploshchad' Lenina, 3

kirill.oparin@hotmail.com

Abstract.

The article studies support systems in field of diagnostics of person psycho-physiological qualities. The subject of the research is the use of neural networks in the development of tests for evaluation of the psycho-physiological state of a person. In this paper the authors examine the possibility of using neural networks to assess the psycho-physiological state of a person applying the achievements obtained by other researchers using neural networks to solve the problems of medical diagnostic, such as in the diagnosis of myocardial infarction or in recognition of emotions based on psycho- physiological parameters. The authors used mathematical modeling methods, such as methods of probability theory, mathematical statistics, artificial intelligence, methods of forecasting and decision-making. The study shows that neural network is an effective tool for the study of such stochastic systems as human. Using neural networks in systems of psycho- physiological diagnosis improves the accuracy of diagnosis by uncovering hidden relationships between different human systems. The ability to use neural networks for the treatment of psycho-physiological test results was confirmed using a generalized description of a neural network and examples of input and output neural network vectors for processing results of the test а reaction to moving object.

Keywords: diagnostics, psycho- physiological qualities of man, psycho-physiological tests, decision support, neural network, neurophysiology, reaction to moving object, tapping test, LVQ neural network, non-parametric model of learning

DOI:

10.7256/2306-4196.2016.2.18155

Article was received:

28-02-2016


Review date:

28-02-2016


Publish date:

03-03-2016


This article written in Russian. You can find full text of article in Russian here .

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