Self-adjusted Data-Driven System for Prediction of Human Performance

- Burov, O. Yu. (orcid.org/0000-0003-0733-1120), Lavrov, Evgeniy, Pasko, Nadiia, Hlazunova, Olena, Lavrova, Olga, Kyzenko, Vasyl (orcid.org/0000-0001-7835-9150) and Dolgikh, Yana (2020) Self-adjusted Data-Driven System for Prediction of Human Performance In: Integrating People and Intelligent Systems: Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020), February 19–21, 2020, Modena, Italy., 19-21 лют. 2020 р., c. Modena, Italy.

[img] Text
KVI 2020_01 Italy.pdf

Download (218kB)

Abstract

Design principles and the data-driven system to assess and to predict an operator readiness-to-perform are disc used in the article. Principles of construction and performance of the system are formulated. The main focus is on data organization (timeline, date set for the model construction) and adaptive algorithm construction. High level of the prediction accuracy for an operator readiness-to-perform (85–90%) was achieved because of use data stored (parameters of time and cognitive tasks performance by user) the system to control its performance, as well as its self-adjusted algorithm of functioning.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Бібліографічний опис: Lavrov, E.; Pasko, N.; Hlazunova, O.; Lavrova, O.; Kyzenko, V., & Dolgikh, Ya. Self-adjusted Data-Driven System for Prediction of Human Performance. Integrating People and Intelligent Systems: Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020), February 19–21, 2020, Modena, Italy. Springer Nature Switzerland AG, 2020, Vol 1131. Pp 282–287. Series «Advances in Intelligent Systems and Computing». (https://doi.org/10.1007/978-3-030-39512-4). ISSN 2194-5365. ISBN 978-3-030-39512-4.
Keywords: data-driven; cognitive performance; self-adjustment; adaptive models.
Subjects: Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 314/316 Society
Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 33 Economics. Economic science
Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 5 Мathematics. natural sciences > 51 Mathematics
Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 6 Applied Sciences. Medicine. Technology > 67 Various industries, trades and crafts
Divisions: Institute of Pedagogics > Didactics Department
Depositing User: К. пед. н. Сергій Володимирович Косянчук
Date Deposited: 05 Feb 2020 17:38
Last Modified: 17 Apr 2020 20:48
URI: http://lib.iitta.gov.ua/id/eprint/719076

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item