Intelligent Decision Support in Complex Socio-Economic Systems

DOI

10.2991/csit-19.2019.30How to use a DOI?

Keywords

expert systems technologies, decision support, Data Mining, professionally important qualities, formalization of knowledge

Abstract

This article considers problems of organizing decision-making support for improving psychophysical readiness of persons for professional activity. Current state of the art, data properties used for the analysis and their features are presented. Classification signs of labor activity, classification of physical exercises, examples of professionally applied physical training of different students as well as tests for evaluation of professional performance are shown. The statement of the problem, mathematical setting of this problem and the process of collecting and processing data for recommendations formation are discussed. The proposed methodology includes collection and preparation of data for analysis, identification of new knowledge based on similarity of objects using clustering, their integration with expert knowledge, formalization of knowledge and formation of the knowledge base, obtaining solutions while making use of knowledge and inference engine. Tools for data mining, namely the analytical platform Deductor Studio, are shown. The results of experimental studies based on the proposed method are provided. Recommendations for improvement of the psychophysical readiness of persons for professional activities taking into account the results of cauterization are considered.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nafisa Yusupova
AU  - Aygul Agadullina
AU  - Tatyana Naumova
AU  - Ekaterina Sazonova
AU  - Olga Smetanina
PY  - 2019/12
DA  - 2019/12
TI  - Intelligent Decision Support in Complex Socio-Economic Systems
BT  - Proceedings of the 21st International Workshop on Computer Science and Information Technologies (CSIT 2019)
PB  - Atlantis Press
SP  - 171
EP  - 178
SN  - 2589-4900
UR  - https://doi.org/10.2991/csit-19.2019.30
DO  - 10.2991/csit-19.2019.30
ID  - Yusupova2019/12
ER  -