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www.T-Science.org       p-ISSN 2308-4944 (print)       e-ISSN 2409-0085 (online)
SOI: 1.1/TAS         DOI: 10.15863/TAS

Journal Archive

ISJ Theoretical & Applied Science 02(34) 2016

ISPC Technology and Innovation, Philadelphia, USA

* Scientific Article * Impact Factor 6.630


Haritonova LP

ON THE ISSUE OF MATHEMATICAL MODELING FOR COMPETITIVE ADVANTAGES OF UNIVERSITY GRADUATES AND INTENSIFICATIONN OF BRAIN ACTIVITY, INCLUDING THE STUDY OF HIGHER MATHEMATICS.

Full Article: PDF

Scientific Object Identifier: http://s-o-i.org/1.1/TAS-02-34-22

DOI: http://dx.doi.org/10.15863/TAS.2016.02.34.22

Language: Russian

Citation: Haritonova LP (2016) ON THE ISSUE OF MATHEMATICAL MODELING FOR COMPETITIVE ADVANTAGES OF UNIVERSITY GRADUATES AND INTENSIFICATIONN OF BRAIN ACTIVITY, INCLUDING THE STUDY OF HIGHER MATHEMATICS. ISJ Theoretical & Applied Science, 02 (34): 164-171. Soi: http://s-o-i.org/1.1/TAS-02-34-22 Doi: http://dx.doi.org/10.15863/TAS.2016.02.34.22

Pages: 164-171

Published: 29.02.2016

Abstract: Methods and recommendations for the establishment of the sequence of actions to enhance and stimulate the brain, improvement neural conductibility, development of channels, that connect nerve cells in different parts of the brain together, and helps to improve memory and mental abilities were given. This investigation in particular may be useful for improvement of the learning outcomes (for example on the study of higher mathematics course). It will be used in leading for greater competitive advantages of university graduates in the future. Despite the excellent prospects projected using NBICS - technologies associated with the intensification of natural intelligence, we should not give up now the point of creation of new methods and techniques of teaching, which were based on the previously obtained data. The analysis and comparison of different methods and approaches for modeling as well as the criteria and scale for the assessment and development of competitive advantages of university graduates were made. It was suggested that it will be possible to use the neural network techniques for modeling and prediction of graduate competitiveness. All of this can serve as a basis for improving the competitiveness and hence the rating of universities in general.

Key words: сompetitive advantages, mathematical modeling, development of memory, the activation of human brain activity.


 

 

 

 

 

 

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